chaseharmon/MIT_Course_Catalog · Datasets at Hugging Face

Class Number stringlengths 4 15	Name stringlengths 4 124	Description stringlengths 23 1.14k	Offered bool 2 classes	Term stringclasses 97 values	Level stringclasses 2 values	Units stringclasses 194 values	Prerequisites stringlengths 4 127 ⌀	Equivalents stringlengths 7 63 ⌀	Lab bool 2 classes	Partial Lab bool 2 classes	REST bool 2 classes	GIR stringclasses 7 values	HASS stringclasses 5 values	CI / CI-HW stringclasses 3 values
5.43	Advanced Organic Chemistry	Reaction mechanisms in organic chemistry: methods of investigation, relation of structure to reactivity, and reactive intermediates. Photochemistry and organometallic chemistry, with an emphasis on fundamental reactivity, mechanistic studies, and applications in organic chemistry.	true	Spring	Undergraduate	4-0-8	5.13	null	false	false	false	False	False	False
5.44	Organometallic Chemistry	Examination of the most important transformations of organotransition-metal species. Emphasizes basic mechanisms of their reactions, structure-reactivity relationships, and applications in synthesis.	true	Fall	Graduate	2-0-4	5.061, 5.43, 5.47, or permission of instructor	null	false	false	false	False	False	False
5.45	Heterocyclic Chemistry	Provides an introduction to the chemistry of heterocyclic compounds. Surveys synthesis and reactivity of the major classes of heterocyclic organic compounds. Discusses the importance of these molecules in the pharmaceutical and other industries.	true	Spring	Graduate	2-0-4	5.511 and 5.53	null	false	false	false	False	False	False
5.46	NMR Spectroscopy and Organic Structure Determination	Applications of multinuclear NMR spectroscopy to the study of organic compounds.	true	Spring	Graduate	2-0-4	5.13	null	false	false	false	False	False	False
5.47	Tutorial in Organic Chemistry	Systematic review of fundamental concepts concerned with the structure and transformations of organic molecules. Problem-solving workshop format. The program is intended primarily for first-year graduate students with a strong interest in organic chemistry. Meets during the month of September.	true	Fall	Graduate	2-0-4 [P/D/F]	5.43 and permission of instructor	null	false	false	false	False	False	False
5.48[J]	Protein Folding in Health and Disease	Focuses on understanding the chemical and biological mechanisms of protein folding, misfolding, aggregation, and quality control. Topics covered include: molecular mechanisms of protein folding; experimental and computational strategies to study protein folding; how cells fold and quality control proteins; protein misfolding and aggregation; proteostasis and human disease; strategies to address protein folding failures in disease; and protein folding in biotechnology development. Provides state-of-the-art understanding of the field, fosters ability to critically assess and use the literature, and empowers students to study and address protein folding issues in their research and beyond.	true	Spring	Graduate	3-0-3	(5.07 or 7.05) and permission of instructor	7.88[J]	false	false	false	False	False	False
5.49	Chemical Microbiology	Focuses on molecular understanding of fundamental processes central to microbial physiology and infectious disease. Topics covered vary and may include (i) secondary metabolite biosynthesis and function, (ii) small molecule mediators of microbe-microbe and microbe-host interactions, (iii) membrane assembly, (iv) metal homeostasis and regulation, (v) antibiotics and antibiotic resistance, (vi) chemistry of the microbiome, and (vii) molecular basis of host-pathogen interactions. Integrates experimental approaches and primary literature.	true	Spring	Graduate	3-0-3	(5.07 or 7.05) and permission of instructor	null	false	false	false	False	False	False
5.511	Synthetic Organic Chemistry I	Presents and discusses important topics in modern synthetic organic chemistry, with the objective of developing problem-solving skills for the design of synthetic routes to complex molecules.	true	Fall	Graduate	2-0-4	5.43 and permission of instructor	null	false	false	false	False	False	False
5.512	Synthetic Organic Chemistry II	General methods and strategies for the synthesis of complex organic compounds.	true	Spring	Graduate	2-0-4	5.511	null	false	false	false	False	False	False
5.52	Tutorial in Chemical Biology	Provides an overview of the core principles of chemistry that underlie biological systems. Students explore research topics and methods in chemical biology by participating in laboratory rotations, then present on experiments performed during each rotation. Intended for first-year graduate students with a strong interest in chemical biology.	true	Fall	Graduate	2-2-8	Permission of instructor	null	false	false	false	False	False	False
5.53	Molecular Structure and Reactivity	Reaction mechanisms in organic chemistry: methods of investigation, relation of structure to reactivity, and reactive intermediates.	true	Fall	Graduate	3-0-9	5.43, 5.601, and 5.602	null	false	false	false	False	False	False
5.54[J]	Advances in Chemical Biology	Introduction to current research at the interface of chemistry, biology, and bioengineering. Topics include imaging of biological processes, metabolic pathway engineering, protein engineering, mechanisms of DNA damage, RNA structure and function, macromolecular machines, protein misfolding and disease, metabolomics, and methods for analyzing signaling network dynamics. Lectures are interspersed with class discussions and student presentations based on current literature.	true	Fall	Graduate	3-0-9	5.07, 5.13, 7.06, and permission of instructor	7.540[J], 20.554[J]	false	false	false	False	False	False
5.55	NMR Spectroscopy and Biochemical Structure Determination	Practical nuclear magnetic resonance (NMR) spectroscopy applied to problems in biochemistry and chemical biology.	true	Spring	Graduate	2-0-4	(5.07 and 5.08) or permission of instructor	null	false	false	false	False	False	False
5.56	Molecular Structure and Reactivity II	Application of physical principles and methods to contemporary problems of interest in organic and polymer chemistry.	true	Spring	Graduate	2-0-4	5.53 or permission of instructor	null	false	false	false	False	False	False
5.561	Chemistry in Industry	Examination of recent advances in organic, biological, and inorganic and physical chemical research in industry. Taught in seminar format with participation by scientists from industrial research laboratories.	true	Spring	Graduate	2-0-4 [P/D/F]	5.03, 5.13, and (5.07 or 7.05)	null	false	false	false	False	False	False
5.601	Thermodynamics I	Basic thermodynamics: state of a system, state variables. Work, heat, first law of thermodynamics, thermochemistry. Second and third law of thermodynamics: entropy and free energy, including the molecular basis for these thermodynamic functions. Equilibrium properties of macroscopic systems. Special attention to thermodynamics related to global energy issues and biological systems. Combination of 5.601 and 5.602 counts as a REST subject.	true	Fall, Spring	Undergraduate	2-0-4	Calculus II (GIR) and Chemistry (GIR)	null	false	false	false	False	False	False
5.602	Thermodynamics II and Kinetics	Free energy and chemical potential. Phase equilibrium and properties of solutions. Chemical equilibrium of reactions. Rates of chemical reactions. Special attention to thermodynamics related to global energy issues and biological systems. Combination of 5.601 and 5.602 counts as a REST subject.	true	Fall, Spring	Undergraduate	2-0-4	5.601	null	false	false	false	False	False	False
5.611	Introduction to Spectroscopy	Introductory quantum chemistry; particles and waves; wave mechanics; harmonic oscillator; applications to IR, Microwave and NMR spectroscopy. Combination of 5.611 and 5.612 counts as a REST subject.	true	Fall	Undergraduate	2-0-4	Calculus II (GIR), Chemistry (GIR), and Physics II (GIR)	null	false	false	false	False	False	False
5.612	Electronic Structure of Molecules	Introductory electronic structure; atomic structure and the Periodic Table; valence and molecular orbital theory; molecular structure, and photochemistry. Combination of 5.611 and 5.612 counts as a REST subject.	true	Fall	Undergraduate	2-0-4	5.611	null	false	false	false	False	False	False
5.62	Physical Chemistry	Elementary statistical mechanics; transport properties; kinetic theory; solid state; reaction rate theory; and chemical reaction dynamics.	true	Spring	Undergraduate	4-0-8	5.601, 5.602, 5.611, and 5.612	null	false	false	false	False	False	False
5.64[J]	Advances in Interdisciplinary Science in Human Health and Disease	Introduces major principles, concepts, and clinical applications of biophysics, biophysical chemistry, and systems biology. Emphasizes biological macromolecular interactions, biochemical reaction dynamics, and genomics. Discusses current technological frontiers and areas of active research at the interface of basic and clinical science. Provides integrated, interdisciplinary training and core experimental and computational methods in molecular biochemistry and genomics.	true	Spring	Graduate	3-0-9	5.13, 5.601, 5.602, and (5.07 or 7.05)	HST.539[J]	false	false	false	False	False	False
5.68[J]	Kinetics of Chemical Reactions	Experimental and theoretical aspects of chemical reaction kinetics, including transition-state theories, molecular beam scattering, classical techniques, quantum and statistical mechanical estimation of rate constants, pressure-dependence and chemical activation, modeling complex reacting mixtures, and uncertainty/ sensitivity analyses. Reactions in the gas phase, liquid phase, and on surfaces are discussed with examples drawn from atmospheric, combustion, industrial, catalytic, and biological chemistry.	true	Fall	Graduate	3-0-6	5.62, 10.37, or 10.65	10.652[J]	false	false	false	False	False	False
5.697[J]	Computational Chemistry	Addresses both the theory and application of first-principles computer simulations methods (i.e., quantum, chemical, or electronic structure), including Hartree-Fock theory, density functional theory, and correlated wavefunction methods. Covers enhanced sampling, ab initio molecular dynamics, and transition-path-finding approaches as well as errors and accuracy in total and free energies. Discusses applications such as the study and prediction of properties of chemical systems, including heterogeneous, molecular, and biological catalysts (enzymes), and physical properties of materials. Students taking graduate version complete additional assignments. Limited to 35; no listeners.	true	Fall	Undergraduate	3-0-9	Permission of instructor	10.437[J]	false	false	false	False	False	False
5.698[J]	Computational Chemistry	Addresses both the theory and application of first-principles computer simulations methods (i.e., quantum, chemical, or electronic structure), including Hartree-Fock theory, density functional theory, and correlated wavefunction methods. Covers enhanced sampling, ab initio molecular dynamics, and transition-path-finding approaches as well as errors and accuracy in total and free energies. Discusses applications such as the study and prediction of properties of chemical systems, including heterogeneous, molecular, and biological catalysts (enzymes), and physical properties of materials. Students taking graduate version complete additional assignments. Limited to 35; no listeners.	true	Fall	Graduate	3-0-9	Permission of instructor	10.637[J]	false	false	false	False	False	False
5.70[J]	Statistical Thermodynamics	Develops classical equilibrium statistical mechanical concepts for application to chemical physics problems. Basic concepts of ensemble theory formulated on the basis of thermodynamic fluctuations. Examples of applications include Ising models, lattice models of binding, ionic and non-ionic solutions, liquid theory, polymer and protein conformations, phase transition, and pattern formation. Introduces computational techniques with examples of liquid and polymer simulations.	true	Fall	Graduate	3-0-9	5.601 or permission of instructor	10.546[J]	false	false	false	False	False	False
5.72	Statistical Mechanics	Principles and methods of statistical mechanics. Classical and quantum statistics, grand ensembles, fluctuations, molecular distribution functions, and other topics in equilibrium statistical mechanics. Topics in thermodynamics and statistical mechanics of irreversible processes.	true	Spring	Graduate	2-0-4	5.70 or permission of instructor	null	false	false	false	False	False	False
5.73	Introductory Quantum Mechanics I	Presents the fundamental concepts of quantum mechanics: wave properties, uncertainty principles, Schrodinger equation, and operator and matrix methods. Includes applications to one-dimensional potentials (harmonic oscillator), three-dimensional centrosymetric potentials (hydrogen atom), and angular momentum and spin. Approximation methods include WKB, variational principle, and perturbation theory.	true	Fall, Fall, IAP, Spring, Summer	Undergraduate	3-0-9	5.611, 5.612, 8.03, and 18.03	null	false	false	false	False	False	False
5.74	Introductory Quantum Mechanics II	Time-dependent quantum mechanics and spectroscopy. Topics include perturbation theory, two-level systems, light-matter interactions, relaxation in quantum systems, correlation functions and linear response theory, and nonlinear spectroscopy.	true	Spring	Graduate	3-0-9	5.73	null	false	false	false	False	False	False
5.78	Biophysical Chemistry Techniques	Presents principles of macromolecular crystallography that are essential for structure determinations. Topics include crystallization, diffraction theory, symmetry and space groups, data collection, phase determination methods, model building, and refinement. Discussion of crystallography theory complemented with exercises such as crystallization, data processing, and model building. Meets with 7.71 when offered concurrently. Enrollment limited.	false	Spring	Graduate	2-0-4	5.07 or 7.05	null	false	false	false	False	False	False
5.80	Advanced Topics of Current Special Interest	Advanced topics of current special interest.	true	Fall, Spring	Graduate	rranged	null	null	false	false	false	False	False	False
5.81[J]	United States Energy Policy: Lessons Learned for the Future	Compares the US policy responses, from the Nixon administration to the current administration, on issues ranging from oil import dependence to nuclear nonproliferation. Examines what lessons were learned from these issues and how they have shaped the country's current climate change policy. Prepares students to be informed and effective participants in policy deliberations that require difficult decisions and trade-offs. Addresses both domestic and international policy aspects. Students taking graduate version complete additional assignments.	true	Fall	Graduate	2-0-4	null	15.029[J]	false	false	false	False	False	False
5.811[J]	United States Energy Policy: Lessons Learned for the Future	Compares the US policy responses, from the Nixon administration to the current administration, on issues ranging from oil import dependence to nuclear nonproliferation. Examines what lessons were learned from these issues and how they have shaped the country's current climate change policy. Prepares students to be informed and effective participants in policy deliberations that require difficult decisions and trade-offs. Addresses both domestic and international policy aspects. Students taking graduate version complete additional assignments.	true	Fall	Undergraduate	2-0-4	null	15.0291[J]	false	false	false	False	False	False
5.812[J]	Principles of Innovation (New)	Presents the key elements required for new technical ideas and business practices to be successfully deployed in an open economy, subject to international trade and external environmental costs. Examines the challenges of climate change and increased international competitiveness as they relate to innovation. Offers recommendations for major policy changes to how innovation is encouraged in the United States and the global economy. Students taking graduate version complete additional assignments.	true	Spring	Undergraduate	2-0-4	null	10.258[J]	false	false	false	False	False	False
5.82[J]	Principles of Innovation (New)	Presents the key elements required for new technical ideas and business practices to be successfully deployed in an open economy, subject to international trade and external environmental costs. Examines the challenges of climate change and increased international competitiveness as they relate to innovation. Offers recommendations for major policy changes to how innovation is encouraged in the United States and the global economy. Students taking graduate version complete additional assignments.	true	Spring	Graduate	2-0-4	null	10.582[J]	false	false	false	False	False	False
5.83	Advanced NMR Spectroscopy	Offers a classical and quantum mechanical description of nuclear magnetic resonance (NMR) spectroscopy. The former includes key concepts such as nuclear spin magnetic moment, Larmor precession, Bloch equations, the rotating frame, radio-frequency pulses, vector model of pulsed NMR, Fourier transformation in 1D and nD NMR, orientation dependence of nuclear spin frequencies, and NMR relaxation. The latter covers nuclear spin Hamiltonians, density operator and its time evolution, the interaction representation, Average Hamiltonian Theory for multi-pulse experiments, and analysis of some common pulse sequences in solution and solid-state NMR.	true	Spring	Graduate	2-0-4	5.73 or permission of instructor	null	false	false	false	False	False	False
5.891	Independent Study in Chemistry for Undergraduates	Program of independent study under direction of Chemistry faculty member. May not substitute for required courses for the Chemistry major or minor.	true	Fall, IAP, Spring, Summer	Undergraduate	rranged	null	null	false	false	false	False	False	False
5.892	Independent Study in Chemistry for Undergraduates	Program of independent study under direction of Chemistry faculty member. May not substitute for required courses for the Chemistry major or minor.	true	Fall, IAP, Spring, Summer	Undergraduate	rranged [P/D/F]	null	null	false	false	false	False	False	False
5.893	Practical Internship Experience in Chemistry	For Course 5 and 5-7 students participating in curriculum-related off-campus internship experiences in chemistry. Before enrolling, students must consult the Chemistry Education Office for details on procedures and restrictions, and have approval from their faculty advisor. Subject to department approval. Upon completion, the student must submit a write-up of the experience, approved by their faculty advisor.	true	Summer	Undergraduate	0-1-0 [P/D/F]	null	null	false	false	false	False	False	False
5.90	Problems in Chemistry	Directed research and study of special chemical problems. For Chemistry graduate students only.	true	Fall, Spring, Summer	Graduate	rranged [P/D/F]	Permission of instructor	null	false	false	false	False	False	False
5.91	Teaching Experience in the Chemical Sciences	For students in the chemistry graduate program while teaching. Classroom or laboratory teaching under the supervision of a faculty member and classroom-based instruction on timely topics related to education and modern teaching practices. Limited to chemistry graduate students who are teaching the same term.	true	Fall, Spring	Graduate	rranged [P/D/F]	Permission of instructor	null	false	false	false	False	False	False
5.913	Seminar in Organic Chemistry	Discusses current journal publications in organic chemistry.	true	Fall, Spring	Graduate	1-0-0 [P/D/F]	Permission of instructor	null	false	false	false	False	False	False
5.921	Seminar in Chemical Biology	Discusses topics of current interest in chemical biology.	true	Fall, Spring	Graduate	1-0-0 [P/D/F]	Permission of instructor	null	false	false	false	False	False	False
5.931	Seminar in Physical Chemistry	Discusses topics of current interest in physical chemistry.	true	Fall, Spring	Graduate	1-0-0 [P/D/F]	5.60	null	false	false	false	False	False	False
5.941	Seminar in Inorganic Chemistry	Discusses current research in inorganic chemistry.	true	Fall, Spring	Graduate	1-0-0 [P/D/F]	5.03	null	false	false	false	False	False	False
5.95[J]	Teaching College-Level Science and Engineering	Participatory seminar focuses on the knowledge and skills necessary for teaching science and engineering in higher education. Topics include theories of adult learning; course development; promoting active learning, problemsolving, and critical thinking in students; communicating with a diverse student body; using educational technology to further learning; lecturing; creating effective tests and assignments; and assessment and evaluation. Students research and present a relevant topic of particular interest. Appropriate for both novices and those with teaching experience.	true	Fall	Graduate	2-0-2 [P/D/F]	null	1.95[J], 7.59[J], 8.395[J], 18.094[J]	false	false	false	False	False	False
5.961[J]	Leadership and Professional Strategies & Skills Training (LEAPS), Part I: Advancing Your Professional Strategies and Skills	Part I (of two parts) of the LEAPS graduate career development and training series. Topics include: navigating and charting an academic career with confidence; convincing an audience with clear writing and arguments; mastering public speaking and communications; networking at conferences and building a brand; identifying transferable skills; preparing for a successful job application package and job interviews; understanding group dynamics and different leadership styles; leading a group or team with purpose and confidence. Postdocs encouraged to attend as non-registered participants. Limited to 80.	true	Spring	Graduate	2-0-1 [P/D/F]	null	8.396[J], 9.980[J], 12.396[J], 18.896[J]	false	false	false	False	False	False
5.962[J]	Leadership and Professional Strategies & Skills Training (LEAPS), Part II: Developing Your Leadership Competencies	Part II (of two parts) of the LEAPS graduate career development and training series. Topics covered include gaining self awareness and awareness of others, and communicating with different personality types; learning about team building practices; strategies for recognizing and resolving conflict and bias; advocating for diversity and inclusion; becoming organizationally savvy; having the courage to be an ethical leader; coaching, mentoring, and developing others; championing, accepting, and implementing change. Postdocs encouraged to attend as non-registered participants. Limited to 80.	true	Spring	Graduate	2-0-1 [P/D/F]	null	8.397[J], 9.981[J], 12.397[J], 18.897[J]	false	false	false	False	False	False
5.S00	Special Subject in Chemistry	Organized lecture, subject consisting of material in the broadly-defined field of chemistry not offered in regularly scheduled subjects.	true	Fall	Graduate	rranged	null	null	false	false	false	False	False	False
5.S64	Special Subject in Chemistry	Organized lecture consisting of material in the broadly-defined field of chemistry not offered in regularly scheduled subjects.	true	Spring	Graduate	2-0-4	null	null	false	false	false	False	False	False
5.S72	Special Subject in Chemistry	Organized lecture consisting of material in the broadly defined field of chemistry not offered in regularly scheduled subjects.	false	Spring	Graduate	3-0-9	null	null	false	false	false	False	False	False
5.S75	Special Subject in Chemistry	Organized lecture consisting of material in the broadly-defined field of chemistry not offered in regularly scheduled subjects.	true	Spring	Graduate	2-0-4	null	null	false	false	false	False	False	False
5.S95	Special Subject in Chemistry	Organized lecture consisting of material in the broadly-defined field of chemistry not offered in regularly scheduled subjects.	true	Fall, Spring	Graduate	1-0-1 [P/D/F]	null	null	false	false	false	False	False	False
5.THG	Graduate Thesis	Program of research leading to the writing of a PhD thesis; to be arranged by the student and an appropriate MIT faculty member.	true	Fall, IAP, Spring, Summer	Graduate	rranged	Permission of instructor	null	false	false	false	False	False	False
5.THU	Undergraduate Thesis	Program of original research under supervision of a chemistry faculty member, culminating with the preparation of a thesis. Ordinarily requires equivalent of two terms of research with chemistry department faculty member.	true	Fall, IAP, Spring, Summer	Undergraduate	rranged	Permission of instructor	null	false	false	false	False	False	False
5.UAR[J]	Climate and Sustainability Undergraduate Advanced Research	Provides instruction in effective research, experiential projects, internships, and externships, including choosing and refining problems, surveying previous work and publications, industry best practices, design for robustness, technical presentation, authorship and collaboration, and ethics. Supporting content includes background and context pertaining to climate change and sustainability, as well as tools for sustainable design. Focus for project work includes research topics relevant to the MIT Climate & Sustainability Consortium (MCSC). Students engage in extensive written and oral communication exercises, in the context of an approved advanced research project. A total of 12 units of credit is awarded for completion of the spring and subsequent fall term offerings. Application required; consult MCSC website for more information.	true	Fall, Spring	Undergraduate	2-0-4	Permission of instructor	1.UAR[J], 3.UAR[J], 11.UAR[J], 12.UAR[J], 15.UAR[J], 22.UAR[J]	false	false	false	False	False	False
5.UR	Undergraduate Research	Program of research to be arranged by the student and a departmental faculty member. Research can be applied toward undergraduate thesis.	true	Fall, IAP, Spring, Summer	Undergraduate	rranged [P/D/F]	null	null	false	false	false	False	False	False
5.URG	Undergraduate Research	Program of research to be arranged by the student and a departmental faculty member. May be taken for up to 12 units per term, not to exceed a cumulative total of 48 units. A 10-page paper summarizing research is required.	true	Fall, IAP, Spring, Summer	Undergraduate	rranged	null	null	false	false	false	False	False	False
6.100A	Introduction to Computer Science Programming in Python	Introduction to computer science and programming for students with little or no programming experience. Students develop skills to program and use computational techniques to solve problems. Topics include the notion of computation, Python, simple algorithms and data structures, testing and debugging, and algorithmic complexity. Combination of 6.100A and 6.100B or 16.C20 counts as REST subject. Final given in the seventh week of the term.	true	Fall, Spring	Undergraduate	2-0-4	null	null	false	false	false	False	False	False
6.100B	Introduction to Computational Thinking and Data Science	Provides an introduction to using computation to understand real-world phenomena. Topics include plotting, stochastic programs, probability and statistics, random walks, Monte Carlo simulations, modeling data, optimization problems, and clustering. Combination of 6.100A and 6.100B counts as REST subject.	true	Fall, Spring	Undergraduate	2-0-4	6.100A or permission of instructor	null	false	false	false	False	False	False
6.100L	Introduction to Computer Science and Programming	Introduction to computer science and programming for students with no programming experience. Presents content taught in 6.100A over an entire semester. Students develop skills to program and use computational techniques to solve problems. Topics include the notion of computation, Python, simple algorithms and data structures, testing and debugging, and algorithmic complexity. Lectures are viewed outside of class; in-class time is dedicated to problem-solving and discussion. Combination of 6.100L and 6.100B or 16.C20 counts as REST subject.	true	Fall, Spring	Undergraduate	2-0-4	null	null	false	false	false	False	False	False
6.1010	Fundamentals of Programming	Introduces fundamental concepts of programming. Designed to develop skills in applying basic methods from programming languages to abstract problems. Topics include programming and Python basics, computational concepts, software engineering, algorithmic techniques, data types, and recursion. Lab component consists of software design, construction, and implementation of design. Enrollment may be limited.	true	Fall, Spring	Undergraduate	2-4-6	6.100A	null	true	false	false	False	False	False
6.1020	Software Construction	Introduces fundamental principles and techniques of software development: how to write software that is safe from bugs, easy to understand, and ready for change. Topics include specifications and invariants; testing, test-case generation, and coverage; abstract data types and representation independence; design patterns for object-oriented programming; concurrent programming, including message passing and shared memory concurrency, and defending against races and deadlock; and functional programming with immutable data and higher-order functions. Includes weekly programming exercises and larger group programming projects.	true	Spring	Undergraduate	3-0-12	6.1010	null	false	false	false	False	False	False
6.1040	Software Design	Provides design-focused instruction on how to build complex software applications. Design topics include classic human-computer interaction (HCI) design tactics (need finding, heuristic evaluation, prototyping, user testing), conceptual design (inventing, modeling and evaluating constituent concepts), social and ethical implications, abstract data modeling, and visual design. Implementation topics include reactive front-ends, web services, and databases. Students work both on individual projects and a larger team project in which they design and build full-stack web applications.	true	Fall	Undergraduate	4-0-14	6.1020 and 6.1200	null	false	false	false	False	False	False
6.1060	Software Performance Engineering	Project-based introduction to building efficient, high-performance and scalable software systems. Topics include performance analysis, algorithmic techniques for high performance, instruction-level optimizations, vectorization, cache and memory hierarchy optimization, and parallel programming.	true	Fall	Undergraduate	3-12-3	6.1020, 6.1210, and 6.1910	null	false	false	false	False	False	False
6.5060	Algorithm Engineering	Covers the theory and practice of algorithms and data structures. Topics include models of computation, algorithm design and analysis, and performance engineering of algorithm implementations. Presents the design and implementation of sequential, parallel, cache-efficient, and external-memory algorithms. Illustrates many of the principles of algorithm engineering in the context of parallel algorithms and graph problems.	true	Spring	Graduate	3-0-9	6.1060 and 6.1220	null	false	false	false	False	False	False
6.5080	Multicore Programming	Introduces principles and core techniques for programming multicore machines. Topics include locking, scalability, concurrent data structures, multiprocessor scheduling, load balancing, and state-of-the-art synchronization techniques, such as transactional memory. Includes sequence of programming assignments on a large multicore machine, culminating with the design of a highly concurrent application. Students taking graduate version complete additional assignments.	true	Spring	Graduate	4-0-8	6.1210	null	false	false	false	False	False	False
6.5081	Multicore Programming	Introduces principles and core techniques for programming multicore machines. Topics include locking, scalability, concurrent data structures, multiprocessor scheduling, load balancing, and state-of-the-art synchronization techniques, such as transactional memory. Includes sequence of programming assignments on a large multicore machine, culminating with the design of a highly concurrent application. Students taking graduate version complete additional assignments.	true	Spring	Undergraduate	4-0-8	6.1210	null	false	false	false	False	False	False
6.1100	Computer Language Engineering	Analyzes issues associated with the implementation of higher-level programming languages. Fundamental concepts, functions, and structures of compilers. The interaction of theory and practice. Using tools in building software. Includes a multi-person project on compiler design and implementation.	true	Spring	Undergraduate	4-4-4	6.1020 and 6.1910	null	false	false	false	False	False	False
6.1120	Dynamic Computer Language Engineering	Studies the design and implementation of modern, dynamic programming languages. Topics include fundamental approaches for parsing, semantics and interpretation, virtual machines, garbage collection, just-in-time machine code generation, and optimization. Includes a semester-long, group project that delivers a virtual machine that spans all of these topics.	true	Fall	Undergraduate	4-4-4	6.1020 or 6.1910	null	false	false	false	False	False	False
6.5110	Foundations of Program Analysis	Presents major principles and techniques for program analysis. Includes formal semantics, type systems and type-based program analysis, abstract interpretation and model checking and synthesis. Emphasis on Haskell and Ocaml, but no prior experience in these languages is assumed. Student assignments include implementing of techniques covered in class, including building simple verifiers.	true	Fall	Graduate	3-0-9	6.1100	null	false	false	false	False	False	False
6.5120	Formal Reasoning About Programs	Surveys techniques for rigorous mathematical reasoning about correctness of software, emphasizing commonalities across approaches. Introduces interactive computer theorem proving with the Coq proof assistant, which is used for all assignments, providing immediate feedback on soundness of logical arguments. Covers common program-proof techniques, including operational semantics, model checking, abstract interpretation, type systems, program logics, and their applications to functional, imperative, and concurrent programs. Develops a common conceptual framework based on invariants, abstraction, and modularity applied to state and labeled transition systems.	true	Spring	Graduate	3-0-9	6.1020 and 6.1200	null	false	false	false	False	False	False
6.5150	Large-scale Symbolic Systems	Concepts and techniques for the design and implementation of large software systems that can be adapted to uses not anticipated by the designer. Applications include compilers, computer-algebra systems, deductive systems, and some artificial intelligence applications. Covers means for decoupling goals from strategy, mechanisms for implementing additive data-directed invocation, work with partially-specified entities, and how to manage multiple viewpoints. Topics include combinators, generic operations, pattern matching, pattern-directed invocation, rule systems, backtracking, dependencies, indeterminacy, memoization, constraint propagation, and incremental refinement. Students taking graduate version complete additional assignments.	true	Spring	Graduate	3-0-9	6.4100 or permission of instructor	null	false	false	false	False	False	False
6.5151	Large-scale Symbolic Systems	Concepts and techniques for the design and implementation of large software systems that can be adapted to uses not anticipated by the designer. Applications include compilers, computer-algebra systems, deductive systems, and some artificial intelligence applications. Covers means for decoupling goals from strategy, mechanisms for implementing additive data-directed invocation, work with partially-specified entities, and how to manage multiple viewpoints. Topics include combinators, generic operations, pattern matching, pattern-directed invocation, rule systems, backtracking, dependencies, indeterminacy, memoization, constraint propagation, and incremental refinement. Students taking graduate version complete additional assignments.	true	Spring	Undergraduate	3-0-9	6.4100 or permission of instructor	null	false	false	false	False	False	False
6.5160[J]	Classical Mechanics: A Computational Approach	Classical mechanics in a computational framework, Lagrangian formulation, action, variational principles, and Hamilton's principle. Conserved quantities, Hamiltonian formulation, surfaces of section, chaos, and Liouville's theorem. Poincaré integral invariants, Poincaré-Birkhoff and KAM theorems. Invariant curves and cantori. Nonlinear resonances, resonance overlap and transition to chaos. Symplectic integration. Adiabatic invariants. Applications to simple physical systems and solar system dynamics. Extensive use of computation to capture methods, for simulation, and for symbolic analysis. Programming experience required.	true	Fall	Graduate	3-3-6	Physics I (GIR), 18.03, and permission of instructor	8.351[J], 12.620[J]	false	false	false	False	False	False
6.1200[J]	Mathematics for Computer Science	Elementary discrete mathematics for science and engineering, with a focus on mathematical tools and proof techniques useful in computer science. Topics include logical notation, sets, relations, elementary graph theory, state machines and invariants, induction and proofs by contradiction, recurrences, asymptotic notation, elementary analysis of algorithms, elementary number theory and cryptography, permutations and combinations, counting tools, and discrete probability.	true	Fall, Spring	Undergraduate	5-0-7	Calculus I (GIR)	18.062[J]	false	false	true	False	False	False
6.120A	Discrete Mathematics and Proof for Computer Science	Subset of elementary discrete mathematics for science and engineering useful in computer science. Topics may include logical notation, sets, done relations, elementary graph theory, state machines and invariants, induction and proofs by contradiction, recurrences, asymptotic notation, elementary analysis of algorithms, elementary number theory and cryptography, permutations and combinations, counting tools.	true	Spring	Undergraduate	3-0-3	Calculus I (GIR)	null	false	false	false	False	False	False
6.1210	Introduction to Algorithms	Introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. Emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems. Enrollment may be limited.	true	Fall, Spring	Undergraduate	5-0-7	6.100A and (6.1200 or (6.120A and (6.3700, 6.3800, 18.05, or 18.600)))	null	false	false	false	False	False	False
6.1220[J]	Design and Analysis of Algorithms	Techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics include sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; greedy algorithms; amortized analysis; graph algorithms; and shortest paths. Advanced topics may include network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.	true	Fall, Spring	Undergraduate	4-0-8	6.1200 and 6.1210	18.410[J]	false	false	false	False	False	False
6.1400[J]	Computability and Complexity Theory	Mathematical introduction to the theory of computing. Rigorously explores what kinds of tasks can be efficiently solved with computers by way of finite automata, circuits, Turing machines, and communication complexity, introducing students to some major open problems in mathematics. Builds skills in classifying computational tasks in terms of their difficulty. Discusses other fundamental issues in computing, including the Halting Problem, the Church-Turing Thesis, the P versus NP problem, and the power of randomness.	true	Spring	Undergraduate	4-0-8	(6.1200 and 6.1210) or permission of instructor	18.400[J]	false	false	false	False	False	False
6.1420	Fixed Parameter and Fine-grained Computation	An overview of the theory of parameterized algorithms and the "problem-centric" theory of fine-grained complexity, both of which reconsider how to measure the difficulty and feasibility of solving computational problems. Topics include: fixed-parameter tractability (FPT) and its characterizations, the W-hierarchy (W[1], W[2], W[P], etc.), 3-sum-hardness, all-pairs shortest paths (APSP)-equivalences, strong exponential time hypothesis (SETH) hardness of problems, and the connections to circuit complexity and other aspects of computing.	false	Fall	Undergraduate	3-0-9	6.1200, 6.1210, and (6.1220, 6.1400, or 18.404)	null	false	false	false	False	False	False
6.5210[J]	Advanced Algorithms	First-year graduate subject in algorithms. Emphasizes fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Surveys a variety of computational models and the algorithms for them. Data structures, network flows, linear programming, computational geometry, approximation algorithms, online algorithms, parallel algorithms, external memory, streaming algorithms.	true	Fall	Graduate	5-0-7	6.1220 and (6.1200, 6.3700, or 18.600)	18.415[J]	false	false	false	False	False	False
6.5220[J]	Randomized Algorithms	Studies how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Models of randomized computation. Data structures: hash tables, and skip lists. Graph algorithms: minimum spanning trees, shortest paths, and minimum cuts. Geometric algorithms: convex hulls, linear programming in fixed or arbitrary dimension. Approximate counting; parallel algorithms; online algorithms; derandomization techniques; and tools for probabilistic analysis of algorithms.	true	Fall	Graduate	5-0-7	(6.1200 or 6.3700) and (6.1220 or 6.5210)	18.416[J]	false	false	false	False	False	False
6.5230	Advanced Data Structures	More advanced and powerful data structures for answering several queries on the same data. Such structures are crucial in particular for designing efficient algorithms. Dictionaries; hashing; search trees. Self-adjusting data structures; linear search; splay trees; dynamic optimality. Integer data structures; word RAM. Predecessor problem; van Emde Boas priority queues; y-fast trees; fusion trees. Lower bounds; cell-probe model; round elimination. Dynamic graphs; link-cut trees; dynamic connectivity. Strings; text indexing; suffix arrays; suffix trees. Static data structures; compact arrays; rank and select. Succinct data structures; tree encodings; implicit data structures. External-memory and cache-oblivious data structures; B-trees; buffer trees; tree layout; ordered-file maintenance. Temporal data structures; persistence; retroactivity.	true	Spring	Graduate	3-0-9	6.1220	null	false	false	false	False	False	False
6.5240	Sublinear Time Algorithms	Sublinear time algorithms understand parameters and properties of input data after viewing only a minuscule fraction of it. Tools from number theory, combinatorics, linear algebra, optimization theory, distributed algorithms, statistics, and probability are covered. Topics include: testing and estimating properties of distributions, functions, graphs, strings, point sets, and various combinatorial objects.	false	Fall	Graduate	3-0-9	6.1220 or permission of instructor	null	false	false	false	False	False	False
6.5250[J]	Distributed Algorithms	Design and analysis of algorithms, emphasizing those suitable for use in distributed networks. Covers various topics including distributed graph algorithms, locality constraints, bandwidth limitations and communication complexity, process synchronization, allocation of computational resources, fault tolerance, and asynchrony. No background in distributed systems required.	true	Spring	Graduate	3-0-9	6.1220	18.437[J]	false	false	false	False	False	False
6.5310	Geometric Folding Algorithms: Linkages, Origami, Polyhedra	Covers discrete geometry and algorithms underlying the reconfiguration of foldable structures, with applications to robotics, manufacturing, and biology. Linkages made from one-dimensional rods connected by hinges: constructing polynomial curves, characterizing rigidity, characterizing unfoldable versus locked, protein folding. Folding two-dimensional paper (origami): characterizing flat foldability, algorithmic origami design, one-cut magic trick. Unfolding and folding three-dimensional polyhedra: edge unfolding, vertex unfolding, gluings, Alexandrov's Theorem, hinged dissections.	true	Spring	Graduate	3-0-9	6.1220 or permission of instructor	null	false	false	false	False	False	False
6.5320	Geometric Computing	Introduction to the design and analysis of algorithms for geometric problems, in low- and high-dimensional spaces. Algorithms: convex hulls, polygon triangulation, Delaunay triangulation, motion planning, pattern matching. Geometric data structures: point location, Voronoi diagrams, Binary Space Partitions. Geometric problems in higher dimensions: linear programming, closest pair problems. High-dimensional nearest neighbor search and low-distortion embeddings between metric spaces. Geometric algorithms for massive data sets: external memory and streaming algorithms. Geometric optimization.	true	Spring	Graduate	3-0-9	6.1220	null	false	false	false	False	False	False
6.5340	Topics in Algorithmic Game Theory	Presents research topics at the interface of computer science and game theory, with an emphasis on algorithms and computational complexity. Explores the types of game-theoretic tools that are applicable to computer systems, the loss in system performance due to the conflicts of interest of users and administrators, and the design of systems whose performance is robust with respect to conflicts of interest inside the system. Algorithmic focus is on algorithms for equilibria, the complexity of equilibria and fixed points, algorithmic tools in mechanism design, learning in games, and the price of anarchy.	true	Spring	Graduate	3-0-9	6.1210 or 6.1220	null	false	false	false	False	False	False
6.5350	Matrix Multiplication and Graph Algorithms	Explores topics around matrix multiplication (MM) and its use in the design of graph algorithms. Focuses on problems such as transitive closure, shortest paths, graph matching, and other classical graph problems. Explores fast approximation algorithms when MM techniques are too expensive.	false	Spring	Graduate	3-0-9	6.1220	null	false	false	false	False	False	False
6.5400[J]	Theory of Computation	A more extensive and theoretical treatment of the material in 6.1400J/18.400J, emphasizing computability and computational complexity theory. Regular and context-free languages. Decidable and undecidable problems, reducibility, recursive function theory. Time and space measures on computation, completeness, hierarchy theorems, inherently complex problems, oracles, probabilistic computation, and interactive proof systems. Students in Course 18 must register for the undergraduate version, 18.404.	true	Fall	Graduate	4-0-8	6.1200 or 18.200	18.4041[J]	false	false	false	False	False	False
6.5410[J]	Advanced Complexity Theory	Current research topics in computational complexity theory. Nondeterministic, alternating, probabilistic, and parallel computation models. Boolean circuits. Complexity classes and complete sets. The polynomial-time hierarchy. Interactive proof systems. Relativization. Definitions of randomness. Pseudo-randomness and derandomizations. Interactive proof systems and probabilistically checkable proofs.	true	Spring	Graduate	3-0-9	18.404	18.405[J]	false	false	false	False	False	False
6.5420	Randomness and Computation	The power and sources of randomness in computation. Connections and applications to computational complexity, computational learning theory, cryptography and combinatorics. Topics include: probabilistic proofs, uniform generation and approximate counting, Fourier analysis of Boolean functions, computational learning theory, expander graphs, pseudorandom generators, derandomization.	true	Spring	Graduate	3-0-9	6.1220 and 18.4041	null	false	false	false	False	False	False
6.5430	Quantum Complexity Theory	Introduction to quantum computational complexity theory, the study of the fundamental capabilities and limitations of quantum computers. Topics include complexity classes, lower bounds, communication complexity, proofs and advice, and interactive proof systems in the quantum world; classical simulation of quantum circuits. The objective is to bring students to the research frontier.	true	Spring	Graduate	3-0-9	6.1400, 18.4041, and 18.435	null	false	false	false	False	False	False
6.1600	Foundations of Computer Security	Fundamental notions and big ideas for achieving security in computer systems. Topics include cryptographic foundations (pseudorandomness, collision-resistant hash functions, authentication codes, signatures, authenticated encryption, public-key encryption), systems ideas (isolation, non-interference, authentication, access control, delegation, trust), and implementation techniques (privilege separation, fuzzing, symbolic execution, runtime defenses, side-channel attacks). Case studies of how these ideas are realized in deployed systems. Lab assignments apply ideas from lectures to learn how to build secure systems and how they can be attacked.	true	Fall	Undergraduate	4-0-8	(6.1210 and (6.1800 or 6.1810)) or permission of instructor	null	false	false	false	False	False	False
6.5610	Applied Cryptography	Covers advanced applications of cryptography, implementation of cryptographic primitives, and cryptanalysis. Topics may include: proof systems; zero knowledge; secret sharing; multiparty computation; fully homomorphic encryption; electronic voting; design of block ciphers and hash functions; elliptic-curve and lattice-based cryptosystems; and algorithms for collision-finding, discrete-log, and factoring. Assignments include a final group project. Topics may vary from year to year.	true	Spring	Graduate	4-0-8	6.1200 and (6.1800 or 6.1810)	null	false	false	false	False	False	False
6.5620[J]	Foundations of Cryptography	A rigorous introduction to modern cryptography. Emphasis on the fundamental cryptographic primitives such as public-key encryption, digital signatures, and pseudo-random number generation, as well as advanced cryptographic primitives such as zero-knowledge proofs, homomorphic encryption, and secure multiparty computation.	true	Fall	Graduate	3-0-9	6.1220, 6.1400, or 18.4041	18.425[J]	false	false	false	False	False	False
6.5630	Advanced Topics in Cryptography	In-depth exploration of recent results in cryptography.	true	Fall	Graduate	3-0-9	6.5620	null	false	false	false	False	False	False
6.5660	Computer Systems Security	Design and implementation of secure computer systems. Lectures cover attacks that compromise security as well as techniques for achieving security, based on recent research papers. Topics include operating system security, privilege separation, capabilities, language-based security, cryptographic network protocols, trusted hardware, and security in web applications and mobile phones. Labs involve implementing and compromising a web application that sandboxes arbitrary code, and a group final project.	true	Spring	Graduate	3-6-3	6.1020 and (6.1800 or 6.1810)	null	false	false	false	False	False	False
6.1800	Computer Systems Engineering	Topics on the engineering of computer software and hardware systems: techniques for controlling complexity; strong modularity using client-server design, operating systems; performance, networks; naming; security and privacy; fault-tolerant systems, atomicity and coordination of concurrent activities, and recovery; impact of computer systems on society. Case studies of working systems and readings from the current literature provide comparisons and contrasts. Includes a single, semester-long design project. Students engage in extensive written communication exercises. Enrollment may be limited.	true	Spring	Undergraduate	5-1-6	6.1910	null	false	false	false	False	False	False
6.1810	Operating System Engineering	Design and implementation of operating systems, and their use as a foundation for systems programming. Topics include virtual memory, file systems, threads, context switches, kernels, interrupts, system calls, interprocess communication, coordination, and interaction between software and hardware. A multi-processor operating system for RISC-V, xv6, is used to illustrate these topics. Individual laboratory assignments involve extending the xv6 operating system, for example to support sophisticated virtual memory features and networking.	true	Fall	Undergraduate	3-0-9	6.1910	null	false	false	false	False	False	False

5.43

Advanced Organic Chemistry

Reaction mechanisms in organic chemistry: methods of investigation, relation of structure to reactivity, and reactive intermediates. Photochemistry and organometallic chemistry, with an emphasis on fundamental reactivity, mechanistic studies, and applications in organic chemistry.

true

Spring

Undergraduate

4-0-8

5.13

null

false

False

5.44

Organometallic Chemistry

Examination of the most important transformations of organotransition-metal species. Emphasizes basic mechanisms of their reactions, structure-reactivity relationships, and applications in synthesis.

true

Fall

Graduate

2-0-4

5.061, 5.43, 5.47, or permission of instructor

null

false

False

5.45

Heterocyclic Chemistry

Provides an introduction to the chemistry of heterocyclic compounds. Surveys synthesis and reactivity of the major classes of heterocyclic organic compounds. Discusses the importance of these molecules in the pharmaceutical and other industries.

true

Spring

Graduate

2-0-4

5.511 and 5.53

null

false

False

5.46

NMR Spectroscopy and Organic Structure Determination

Applications of multinuclear NMR spectroscopy to the study of organic compounds.

true

Spring

Graduate

2-0-4

5.13

null

false

False

5.47

Tutorial in Organic Chemistry

Systematic review of fundamental concepts concerned with the structure and transformations of organic molecules. Problem-solving workshop format. The program is intended primarily for first-year graduate students with a strong interest in organic chemistry. Meets during the month of September.

true

Fall

Graduate

2-0-4 [P/D/F]

5.43 and permission of instructor

null

false

False

5.48[J]

Protein Folding in Health and Disease

Focuses on understanding the chemical and biological mechanisms of protein folding, misfolding, aggregation, and quality control. Topics covered include: molecular mechanisms of protein folding; experimental and computational strategies to study protein folding; how cells fold and quality control proteins; protein misfolding and aggregation; proteostasis and human disease; strategies to address protein folding failures in disease; and protein folding in biotechnology development. Provides state-of-the-art understanding of the field, fosters ability to critically assess and use the literature, and empowers students to study and address protein folding issues in their research and beyond.

true

Spring

Graduate

3-0-3

(5.07 or 7.05) and permission of instructor

7.88[J]

false

False

5.49

Chemical Microbiology

Focuses on molecular understanding of fundamental processes central to microbial physiology and infectious disease. Topics covered vary and may include (i) secondary metabolite biosynthesis and function, (ii) small molecule mediators of microbe-microbe and microbe-host interactions, (iii) membrane assembly, (iv) metal homeostasis and regulation, (v) antibiotics and antibiotic resistance, (vi) chemistry of the microbiome, and (vii) molecular basis of host-pathogen interactions. Integrates experimental approaches and primary literature.

true

Spring

Graduate

3-0-3

(5.07 or 7.05) and permission of instructor

null

false

False

5.511

Synthetic Organic Chemistry I

Presents and discusses important topics in modern synthetic organic chemistry, with the objective of developing problem-solving skills for the design of synthetic routes to complex molecules.

true

Fall

Graduate

2-0-4

5.43 and permission of instructor

null

false

False

5.512

Synthetic Organic Chemistry II

General methods and strategies for the synthesis of complex organic compounds.

true

Spring

Graduate

2-0-4

5.511

null

false

False

5.52

Tutorial in Chemical Biology

Provides an overview of the core principles of chemistry that underlie biological systems. Students explore research topics and methods in chemical biology by participating in laboratory rotations, then present on experiments performed during each rotation. Intended for first-year graduate students with a strong interest in chemical biology.

true

Fall

Graduate

2-2-8

Permission of instructor

null

false

False

5.53

Molecular Structure and Reactivity

Reaction mechanisms in organic chemistry: methods of investigation, relation of structure to reactivity, and reactive intermediates.

true

Fall

Graduate

3-0-9

5.43, 5.601, and 5.602

null

false

False

5.54[J]

Advances in Chemical Biology

Introduction to current research at the interface of chemistry, biology, and bioengineering. Topics include imaging of biological processes, metabolic pathway engineering, protein engineering, mechanisms of DNA damage, RNA structure and function, macromolecular machines, protein misfolding and disease, metabolomics, and methods for analyzing signaling network dynamics. Lectures are interspersed with class discussions and student presentations based on current literature.

true

Fall

Graduate

3-0-9

5.07, 5.13, 7.06, and permission of instructor

7.540[J], 20.554[J]

false

False

5.55

NMR Spectroscopy and Biochemical Structure Determination

Practical nuclear magnetic resonance (NMR) spectroscopy applied to problems in biochemistry and chemical biology.

true

Spring

Graduate

2-0-4

(5.07 and 5.08) or permission of instructor

null

false

False

5.56

Molecular Structure and Reactivity II

Application of physical principles and methods to contemporary problems of interest in organic and polymer chemistry.

true

Spring

Graduate

2-0-4

5.53 or permission of instructor

null

false

False

5.561

Chemistry in Industry

Examination of recent advances in organic, biological, and inorganic and physical chemical research in industry. Taught in seminar format with participation by scientists from industrial research laboratories.

true

Spring

Graduate

2-0-4 [P/D/F]

5.03, 5.13, and (5.07 or 7.05)

null

false

False

5.601

Thermodynamics I

Basic thermodynamics: state of a system, state variables. Work, heat, first law of thermodynamics, thermochemistry. Second and third law of thermodynamics: entropy and free energy, including the molecular basis for these thermodynamic functions. Equilibrium properties of macroscopic systems. Special attention to thermodynamics related to global energy issues and biological systems. Combination of 5.601 and 5.602 counts as a REST subject.

true

Fall, Spring

Undergraduate

2-0-4

Calculus II (GIR) and Chemistry (GIR)

null

false

False

5.602

Thermodynamics II and Kinetics

Free energy and chemical potential. Phase equilibrium and properties of solutions. Chemical equilibrium of reactions. Rates of chemical reactions. Special attention to thermodynamics related to global energy issues and biological systems. Combination of 5.601 and 5.602 counts as a REST subject.

true

Fall, Spring

Undergraduate

2-0-4

5.601

null

false

False

5.611

Introduction to Spectroscopy

Introductory quantum chemistry; particles and waves; wave mechanics; harmonic oscillator; applications to IR, Microwave and NMR spectroscopy. Combination of 5.611 and 5.612 counts as a REST subject.

true

Fall

Undergraduate

2-0-4

Calculus II (GIR), Chemistry (GIR), and Physics II (GIR)

null

false

False

5.612

Electronic Structure of Molecules

Introductory electronic structure; atomic structure and the Periodic Table; valence and molecular orbital theory; molecular structure, and photochemistry. Combination of 5.611 and 5.612 counts as a REST subject.

true

Fall

Undergraduate

2-0-4

5.611

null

false

False

5.62

Physical Chemistry

Elementary statistical mechanics; transport properties; kinetic theory; solid state; reaction rate theory; and chemical reaction dynamics.

true

Spring

Undergraduate

4-0-8

5.601, 5.602, 5.611, and 5.612

null

false

False

5.64[J]

Advances in Interdisciplinary Science in Human Health and Disease

Introduces major principles, concepts, and clinical applications of biophysics, biophysical chemistry, and systems biology. Emphasizes biological macromolecular interactions, biochemical reaction dynamics, and genomics. Discusses current technological frontiers and areas of active research at the interface of basic and clinical science. Provides integrated, interdisciplinary training and core experimental and computational methods in molecular biochemistry and genomics.

true

Spring

Graduate

3-0-9

5.13, 5.601, 5.602, and (5.07 or 7.05)

HST.539[J]

false

False

5.68[J]

Kinetics of Chemical Reactions

Experimental and theoretical aspects of chemical reaction kinetics, including transition-state theories, molecular beam scattering, classical techniques, quantum and statistical mechanical estimation of rate constants, pressure-dependence and chemical activation, modeling complex reacting mixtures, and uncertainty/ sensitivity analyses. Reactions in the gas phase, liquid phase, and on surfaces are discussed with examples drawn from atmospheric, combustion, industrial, catalytic, and biological chemistry.

true

Fall

Graduate

3-0-6

5.62, 10.37, or 10.65

10.652[J]

false

False

5.697[J]

Computational Chemistry

Addresses both the theory and application of first-principles computer simulations methods (i.e., quantum, chemical, or electronic structure), including Hartree-Fock theory, density functional theory, and correlated wavefunction methods. Covers enhanced sampling, ab initio molecular dynamics, and transition-path-finding approaches as well as errors and accuracy in total and free energies. Discusses applications such as the study and prediction of properties of chemical systems, including heterogeneous, molecular, and biological catalysts (enzymes), and physical properties of materials. Students taking graduate version complete additional assignments. Limited to 35; no listeners.

true

Fall

Undergraduate

3-0-9

Permission of instructor

10.437[J]

false

False

5.698[J]

Computational Chemistry

Addresses both the theory and application of first-principles computer simulations methods (i.e., quantum, chemical, or electronic structure), including Hartree-Fock theory, density functional theory, and correlated wavefunction methods. Covers enhanced sampling, ab initio molecular dynamics, and transition-path-finding approaches as well as errors and accuracy in total and free energies. Discusses applications such as the study and prediction of properties of chemical systems, including heterogeneous, molecular, and biological catalysts (enzymes), and physical properties of materials. Students taking graduate version complete additional assignments. Limited to 35; no listeners.

true

Fall

Graduate

3-0-9

Permission of instructor

10.637[J]

false

False

5.70[J]

Statistical Thermodynamics

Develops classical equilibrium statistical mechanical concepts for application to chemical physics problems. Basic concepts of ensemble theory formulated on the basis of thermodynamic fluctuations. Examples of applications include Ising models, lattice models of binding, ionic and non-ionic solutions, liquid theory, polymer and protein conformations, phase transition, and pattern formation. Introduces computational techniques with examples of liquid and polymer simulations.

true

Fall

Graduate

3-0-9

5.601 or permission of instructor

10.546[J]

false

False

5.72

Statistical Mechanics

Principles and methods of statistical mechanics. Classical and quantum statistics, grand ensembles, fluctuations, molecular distribution functions, and other topics in equilibrium statistical mechanics. Topics in thermodynamics and statistical mechanics of irreversible processes.

true

Spring

Graduate

2-0-4

5.70 or permission of instructor

null

false

False

5.73

Introductory Quantum Mechanics I

Presents the fundamental concepts of quantum mechanics: wave properties, uncertainty principles, Schrodinger equation, and operator and matrix methods. Includes applications to one-dimensional potentials (harmonic oscillator), three-dimensional centrosymetric potentials (hydrogen atom), and angular momentum and spin. Approximation methods include WKB, variational principle, and perturbation theory.

true

Fall, Fall, IAP, Spring, Summer

Undergraduate

3-0-9

5.611, 5.612, 8.03, and 18.03

null

false

False

5.74

Introductory Quantum Mechanics II

Time-dependent quantum mechanics and spectroscopy. Topics include perturbation theory, two-level systems, light-matter interactions, relaxation in quantum systems, correlation functions and linear response theory, and nonlinear spectroscopy.

true

Spring

Graduate

3-0-9

5.73

null

false

False

5.78

Biophysical Chemistry Techniques

Presents principles of macromolecular crystallography that are essential for structure determinations. Topics include crystallization, diffraction theory, symmetry and space groups, data collection, phase determination methods, model building, and refinement. Discussion of crystallography theory complemented with exercises such as crystallization, data processing, and model building. Meets with 7.71 when offered concurrently. Enrollment limited.

false

Spring

Graduate

2-0-4

5.07 or 7.05

null

false

False

5.80

Advanced Topics of Current Special Interest

Advanced topics of current special interest.

true

Fall, Spring

Graduate

rranged

null

false

False

5.81[J]

United States Energy Policy: Lessons Learned for the Future

Compares the US policy responses, from the Nixon administration to the current administration, on issues ranging from oil import dependence to nuclear nonproliferation. Examines what lessons were learned from these issues and how they have shaped the country's current climate change policy. Prepares students to be informed and effective participants in policy deliberations that require difficult decisions and trade-offs. Addresses both domestic and international policy aspects. Students taking graduate version complete additional assignments.

true

Fall

Graduate

2-0-4

null

15.029[J]

false

False

5.811[J]

United States Energy Policy: Lessons Learned for the Future

Compares the US policy responses, from the Nixon administration to the current administration, on issues ranging from oil import dependence to nuclear nonproliferation. Examines what lessons were learned from these issues and how they have shaped the country's current climate change policy. Prepares students to be informed and effective participants in policy deliberations that require difficult decisions and trade-offs. Addresses both domestic and international policy aspects. Students taking graduate version complete additional assignments.

true

Fall

Undergraduate

2-0-4

null

15.0291[J]

false

False

5.812[J]

Principles of Innovation (New)

Presents the key elements required for new technical ideas and business practices to be successfully deployed in an open economy, subject to international trade and external environmental costs. Examines the challenges of climate change and increased international competitiveness as they relate to innovation. Offers recommendations for major policy changes to how innovation is encouraged in the United States and the global economy. Students taking graduate version complete additional assignments.

true

Spring

Undergraduate

2-0-4

null

10.258[J]

false

False

5.82[J]

Principles of Innovation (New)

Presents the key elements required for new technical ideas and business practices to be successfully deployed in an open economy, subject to international trade and external environmental costs. Examines the challenges of climate change and increased international competitiveness as they relate to innovation. Offers recommendations for major policy changes to how innovation is encouraged in the United States and the global economy. Students taking graduate version complete additional assignments.

true

Spring

Graduate

2-0-4

null

10.582[J]

false

False

5.83

Advanced NMR Spectroscopy

Offers a classical and quantum mechanical description of nuclear magnetic resonance (NMR) spectroscopy. The former includes key concepts such as nuclear spin magnetic moment, Larmor precession, Bloch equations, the rotating frame, radio-frequency pulses, vector model of pulsed NMR, Fourier transformation in 1D and nD NMR, orientation dependence of nuclear spin frequencies, and NMR relaxation. The latter covers nuclear spin Hamiltonians, density operator and its time evolution, the interaction representation, Average Hamiltonian Theory for multi-pulse experiments, and analysis of some common pulse sequences in solution and solid-state NMR.

true

Spring

Graduate

2-0-4

5.73 or permission of instructor

null

false

False

5.891

Independent Study in Chemistry for Undergraduates

Program of independent study under direction of Chemistry faculty member. May not substitute for required courses for the Chemistry major or minor.

true

Fall, IAP, Spring, Summer

Undergraduate

rranged

null

false

False

5.892

Independent Study in Chemistry for Undergraduates

Program of independent study under direction of Chemistry faculty member. May not substitute for required courses for the Chemistry major or minor.

true

Fall, IAP, Spring, Summer

Undergraduate

rranged [P/D/F]

null

false

False

5.893

Practical Internship Experience in Chemistry

For Course 5 and 5-7 students participating in curriculum-related off-campus internship experiences in chemistry. Before enrolling, students must consult the Chemistry Education Office for details on procedures and restrictions, and have approval from their faculty advisor. Subject to department approval. Upon completion, the student must submit a write-up of the experience, approved by their faculty advisor.

true

Summer

Undergraduate

0-1-0 [P/D/F]

null

false

False

5.90

Problems in Chemistry

Directed research and study of special chemical problems. For Chemistry graduate students only.

true

Fall, Spring, Summer

Graduate

rranged [P/D/F]

Permission of instructor

null

false

False

5.91

Teaching Experience in the Chemical Sciences

For students in the chemistry graduate program while teaching. Classroom or laboratory teaching under the supervision of a faculty member and classroom-based instruction on timely topics related to education and modern teaching practices. Limited to chemistry graduate students who are teaching the same term.

true

Fall, Spring

Graduate

rranged [P/D/F]

Permission of instructor

null

false

False

5.913

Seminar in Organic Chemistry

Discusses current journal publications in organic chemistry.

true

Fall, Spring

Graduate

1-0-0 [P/D/F]

Permission of instructor

null

false

False

5.921

Seminar in Chemical Biology

Discusses topics of current interest in chemical biology.

true

Fall, Spring

Graduate

1-0-0 [P/D/F]

Permission of instructor

null

false

False

5.931

Seminar in Physical Chemistry

Discusses topics of current interest in physical chemistry.

true

Fall, Spring

Graduate

1-0-0 [P/D/F]

5.60

null

false

False

5.941

Seminar in Inorganic Chemistry

Discusses current research in inorganic chemistry.

true

Fall, Spring

Graduate

1-0-0 [P/D/F]

5.03

null

false

False

5.95[J]

Teaching College-Level Science and Engineering

Participatory seminar focuses on the knowledge and skills necessary for teaching science and engineering in higher education. Topics include theories of adult learning; course development; promoting active learning, problemsolving, and critical thinking in students; communicating with a diverse student body; using educational technology to further learning; lecturing; creating effective tests and assignments; and assessment and evaluation. Students research and present a relevant topic of particular interest. Appropriate for both novices and those with teaching experience.

true

Fall

Graduate

2-0-2 [P/D/F]

null

1.95[J], 7.59[J], 8.395[J], 18.094[J]

false

False

5.961[J]

Leadership and Professional Strategies & Skills Training (LEAPS), Part I: Advancing Your Professional Strategies and Skills

Part I (of two parts) of the LEAPS graduate career development and training series. Topics include: navigating and charting an academic career with confidence; convincing an audience with clear writing and arguments; mastering public speaking and communications; networking at conferences and building a brand; identifying transferable skills; preparing for a successful job application package and job interviews; understanding group dynamics and different leadership styles; leading a group or team with purpose and confidence. Postdocs encouraged to attend as non-registered participants. Limited to 80.

true

Spring

Graduate

2-0-1 [P/D/F]

null

8.396[J], 9.980[J], 12.396[J], 18.896[J]

false

False

5.962[J]

Leadership and Professional Strategies & Skills Training (LEAPS), Part II: Developing Your Leadership Competencies

Part II (of two parts) of the LEAPS graduate career development and training series. Topics covered include gaining self awareness and awareness of others, and communicating with different personality types; learning about team building practices; strategies for recognizing and resolving conflict and bias; advocating for diversity and inclusion; becoming organizationally savvy; having the courage to be an ethical leader; coaching, mentoring, and developing others; championing, accepting, and implementing change. Postdocs encouraged to attend as non-registered participants. Limited to 80.

true

Spring

Graduate

2-0-1 [P/D/F]

null

8.397[J], 9.981[J], 12.397[J], 18.897[J]

false

False

5.S00

Special Subject in Chemistry

Organized lecture, subject consisting of material in the broadly-defined field of chemistry not offered in regularly scheduled subjects.

true

Fall

Graduate

rranged

null

false

False

5.S64

Special Subject in Chemistry

Organized lecture consisting of material in the broadly-defined field of chemistry not offered in regularly scheduled subjects.

true

Spring

Graduate

2-0-4

null

false

False

5.S72

Special Subject in Chemistry

Organized lecture consisting of material in the broadly defined field of chemistry not offered in regularly scheduled subjects.

false

Spring

Graduate

3-0-9

null

false

False

5.S75

Special Subject in Chemistry

Organized lecture consisting of material in the broadly-defined field of chemistry not offered in regularly scheduled subjects.

true

Spring

Graduate

2-0-4

null

false

False

5.S95

Special Subject in Chemistry

Organized lecture consisting of material in the broadly-defined field of chemistry not offered in regularly scheduled subjects.

true

Fall, Spring

Graduate

1-0-1 [P/D/F]

null

false

False

5.THG

Graduate Thesis

Program of research leading to the writing of a PhD thesis; to be arranged by the student and an appropriate MIT faculty member.

true

Fall, IAP, Spring, Summer

Graduate

rranged

Permission of instructor

null

false

False

5.THU

Undergraduate Thesis

Program of original research under supervision of a chemistry faculty member, culminating with the preparation of a thesis. Ordinarily requires equivalent of two terms of research with chemistry department faculty member.

true

Fall, IAP, Spring, Summer

Undergraduate

rranged

Permission of instructor

null

false

False

5.UAR[J]

Climate and Sustainability Undergraduate Advanced Research

Provides instruction in effective research, experiential projects, internships, and externships, including choosing and refining problems, surveying previous work and publications, industry best practices, design for robustness, technical presentation, authorship and collaboration, and ethics. Supporting content includes background and context pertaining to climate change and sustainability, as well as tools for sustainable design. Focus for project work includes research topics relevant to the MIT Climate & Sustainability Consortium (MCSC). Students engage in extensive written and oral communication exercises, in the context of an approved advanced research project. A total of 12 units of credit is awarded for completion of the spring and subsequent fall term offerings. Application required; consult MCSC website for more information.

true

Fall, Spring

Undergraduate

2-0-4

Permission of instructor

1.UAR[J], 3.UAR[J], 11.UAR[J], 12.UAR[J], 15.UAR[J], 22.UAR[J]

false

False

5.UR

Undergraduate Research

Program of research to be arranged by the student and a departmental faculty member. Research can be applied toward undergraduate thesis.

true

Fall, IAP, Spring, Summer

Undergraduate

rranged [P/D/F]

null

false

False

5.URG

Undergraduate Research

Program of research to be arranged by the student and a departmental faculty member. May be taken for up to 12 units per term, not to exceed a cumulative total of 48 units. A 10-page paper summarizing research is required.

true

Fall, IAP, Spring, Summer

Undergraduate

rranged

null

false

False

6.100A

Introduction to Computer Science Programming in Python

Introduction to computer science and programming for students with little or no programming experience. Students develop skills to program and use computational techniques to solve problems. Topics include the notion of computation, Python, simple algorithms and data structures, testing and debugging, and algorithmic complexity. Combination of 6.100A and 6.100B or 16.C20 counts as REST subject. Final given in the seventh week of the term.

true

Fall, Spring

Undergraduate

2-0-4

null

false

False

6.100B

Introduction to Computational Thinking and Data Science

Provides an introduction to using computation to understand real-world phenomena. Topics include plotting, stochastic programs, probability and statistics, random walks, Monte Carlo simulations, modeling data, optimization problems, and clustering. Combination of 6.100A and 6.100B counts as REST subject.

true

Fall, Spring

Undergraduate

2-0-4

6.100A or permission of instructor

null

false

False

6.100L

Introduction to Computer Science and Programming

Introduction to computer science and programming for students with no programming experience. Presents content taught in 6.100A over an entire semester. Students develop skills to program and use computational techniques to solve problems. Topics include the notion of computation, Python, simple algorithms and data structures, testing and debugging, and algorithmic complexity. Lectures are viewed outside of class; in-class time is dedicated to problem-solving and discussion. Combination of 6.100L and 6.100B or 16.C20 counts as REST subject.

true

Fall, Spring

Undergraduate

2-0-4

null

false

False

6.1010

Fundamentals of Programming

Introduces fundamental concepts of programming. Designed to develop skills in applying basic methods from programming languages to abstract problems. Topics include programming and Python basics, computational concepts, software engineering, algorithmic techniques, data types, and recursion. Lab component consists of software design, construction, and implementation of design. Enrollment may be limited.

true

Fall, Spring

Undergraduate

2-4-6

6.100A

null

true

false

False

6.1020

Software Construction

Introduces fundamental principles and techniques of software development: how to write software that is safe from bugs, easy to understand, and ready for change. Topics include specifications and invariants; testing, test-case generation, and coverage; abstract data types and representation independence; design patterns for object-oriented programming; concurrent programming, including message passing and shared memory concurrency, and defending against races and deadlock; and functional programming with immutable data and higher-order functions. Includes weekly programming exercises and larger group programming projects.

true

Spring

Undergraduate

3-0-12

6.1010

null

false

False

6.1040

Software Design

Provides design-focused instruction on how to build complex software applications. Design topics include classic human-computer interaction (HCI) design tactics (need finding, heuristic evaluation, prototyping, user testing), conceptual design (inventing, modeling and evaluating constituent concepts), social and ethical implications, abstract data modeling, and visual design. Implementation topics include reactive front-ends, web services, and databases. Students work both on individual projects and a larger team project in which they design and build full-stack web applications.

true

Fall

Undergraduate

4-0-14

6.1020 and 6.1200

null

false

False

6.1060

Software Performance Engineering

Project-based introduction to building efficient, high-performance and scalable software systems. Topics include performance analysis, algorithmic techniques for high performance, instruction-level optimizations, vectorization, cache and memory hierarchy optimization, and parallel programming.

true

Fall

Undergraduate

3-12-3

6.1020, 6.1210, and 6.1910

null

false

False

6.5060

Algorithm Engineering

Covers the theory and practice of algorithms and data structures. Topics include models of computation, algorithm design and analysis, and performance engineering of algorithm implementations. Presents the design and implementation of sequential, parallel, cache-efficient, and external-memory algorithms. Illustrates many of the principles of algorithm engineering in the context of parallel algorithms and graph problems.

true

Spring

Graduate

3-0-9

6.1060 and 6.1220

null

false

False

6.5080

Multicore Programming

Introduces principles and core techniques for programming multicore machines. Topics include locking, scalability, concurrent data structures, multiprocessor scheduling, load balancing, and state-of-the-art synchronization techniques, such as transactional memory. Includes sequence of programming assignments on a large multicore machine, culminating with the design of a highly concurrent application. Students taking graduate version complete additional assignments.

true

Spring

Graduate

4-0-8

6.1210

null

false

False

6.5081

Multicore Programming

Introduces principles and core techniques for programming multicore machines. Topics include locking, scalability, concurrent data structures, multiprocessor scheduling, load balancing, and state-of-the-art synchronization techniques, such as transactional memory. Includes sequence of programming assignments on a large multicore machine, culminating with the design of a highly concurrent application. Students taking graduate version complete additional assignments.

true

Spring

Undergraduate

4-0-8

6.1210

null

false

False

6.1100

Computer Language Engineering

Analyzes issues associated with the implementation of higher-level programming languages. Fundamental concepts, functions, and structures of compilers. The interaction of theory and practice. Using tools in building software. Includes a multi-person project on compiler design and implementation.

true

Spring

Undergraduate

4-4-4

6.1020 and 6.1910

null

false

False

6.1120

Dynamic Computer Language Engineering

Studies the design and implementation of modern, dynamic programming languages. Topics include fundamental approaches for parsing, semantics and interpretation, virtual machines, garbage collection, just-in-time machine code generation, and optimization. Includes a semester-long, group project that delivers a virtual machine that spans all of these topics.

true

Fall

Undergraduate

4-4-4

6.1020 or 6.1910

null

false

False

6.5110

Foundations of Program Analysis

Presents major principles and techniques for program analysis. Includes formal semantics, type systems and type-based program analysis, abstract interpretation and model checking and synthesis. Emphasis on Haskell and Ocaml, but no prior experience in these languages is assumed. Student assignments include implementing of techniques covered in class, including building simple verifiers.

true

Fall

Graduate

3-0-9

6.1100

null

false

False

6.5120

Formal Reasoning About Programs

Surveys techniques for rigorous mathematical reasoning about correctness of software, emphasizing commonalities across approaches. Introduces interactive computer theorem proving with the Coq proof assistant, which is used for all assignments, providing immediate feedback on soundness of logical arguments. Covers common program-proof techniques, including operational semantics, model checking, abstract interpretation, type systems, program logics, and their applications to functional, imperative, and concurrent programs. Develops a common conceptual framework based on invariants, abstraction, and modularity applied to state and labeled transition systems.

true

Spring

Graduate

3-0-9

6.1020 and 6.1200

null

false

False

6.5150

Large-scale Symbolic Systems

Concepts and techniques for the design and implementation of large software systems that can be adapted to uses not anticipated by the designer. Applications include compilers, computer-algebra systems, deductive systems, and some artificial intelligence applications. Covers means for decoupling goals from strategy, mechanisms for implementing additive data-directed invocation, work with partially-specified entities, and how to manage multiple viewpoints. Topics include combinators, generic operations, pattern matching, pattern-directed invocation, rule systems, backtracking, dependencies, indeterminacy, memoization, constraint propagation, and incremental refinement. Students taking graduate version complete additional assignments.

true

Spring

Graduate

3-0-9

6.4100 or permission of instructor

null

false

False

6.5151

Large-scale Symbolic Systems

Concepts and techniques for the design and implementation of large software systems that can be adapted to uses not anticipated by the designer. Applications include compilers, computer-algebra systems, deductive systems, and some artificial intelligence applications. Covers means for decoupling goals from strategy, mechanisms for implementing additive data-directed invocation, work with partially-specified entities, and how to manage multiple viewpoints. Topics include combinators, generic operations, pattern matching, pattern-directed invocation, rule systems, backtracking, dependencies, indeterminacy, memoization, constraint propagation, and incremental refinement. Students taking graduate version complete additional assignments.

true

Spring

Undergraduate

3-0-9

6.4100 or permission of instructor

null

false

False

6.5160[J]

Classical Mechanics: A Computational Approach

Classical mechanics in a computational framework, Lagrangian formulation, action, variational principles, and Hamilton's principle. Conserved quantities, Hamiltonian formulation, surfaces of section, chaos, and Liouville's theorem. Poincaré integral invariants, Poincaré-Birkhoff and KAM theorems. Invariant curves and cantori. Nonlinear resonances, resonance overlap and transition to chaos. Symplectic integration. Adiabatic invariants. Applications to simple physical systems and solar system dynamics. Extensive use of computation to capture methods, for simulation, and for symbolic analysis. Programming experience required.

true

Fall

Graduate

3-3-6

Physics I (GIR), 18.03, and permission of instructor

8.351[J], 12.620[J]

false

False

6.1200[J]

Mathematics for Computer Science

Elementary discrete mathematics for science and engineering, with a focus on mathematical tools and proof techniques useful in computer science. Topics include logical notation, sets, relations, elementary graph theory, state machines and invariants, induction and proofs by contradiction, recurrences, asymptotic notation, elementary analysis of algorithms, elementary number theory and cryptography, permutations and combinations, counting tools, and discrete probability.

true

Fall, Spring

Undergraduate

5-0-7

Calculus I (GIR)

18.062[J]

false

true

False

6.120A

Discrete Mathematics and Proof for Computer Science

Subset of elementary discrete mathematics for science and engineering useful in computer science. Topics may include logical notation, sets, done relations, elementary graph theory, state machines and invariants, induction and proofs by contradiction, recurrences, asymptotic notation, elementary analysis of algorithms, elementary number theory and cryptography, permutations and combinations, counting tools.

true

Spring

Undergraduate

3-0-3

Calculus I (GIR)

null

false

False

6.1210

Introduction to Algorithms

Introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. Emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems. Enrollment may be limited.

true

Fall, Spring

Undergraduate

5-0-7

6.100A and (6.1200 or (6.120A and (6.3700, 6.3800, 18.05, or 18.600)))

null

false

False

6.1220[J]

Design and Analysis of Algorithms

Techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics include sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; greedy algorithms; amortized analysis; graph algorithms; and shortest paths. Advanced topics may include network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.

true

Fall, Spring

Undergraduate

4-0-8

6.1200 and 6.1210

18.410[J]

false

False

6.1400[J]

Computability and Complexity Theory

Mathematical introduction to the theory of computing. Rigorously explores what kinds of tasks can be efficiently solved with computers by way of finite automata, circuits, Turing machines, and communication complexity, introducing students to some major open problems in mathematics. Builds skills in classifying computational tasks in terms of their difficulty. Discusses other fundamental issues in computing, including the Halting Problem, the Church-Turing Thesis, the P versus NP problem, and the power of randomness.

true

Spring

Undergraduate

4-0-8

(6.1200 and 6.1210) or permission of instructor

18.400[J]

false

False

6.1420

Fixed Parameter and Fine-grained Computation

An overview of the theory of parameterized algorithms and the "problem-centric" theory of fine-grained complexity, both of which reconsider how to measure the difficulty and feasibility of solving computational problems. Topics include: fixed-parameter tractability (FPT) and its characterizations, the W-hierarchy (W[1], W[2], W[P], etc.), 3-sum-hardness, all-pairs shortest paths (APSP)-equivalences, strong exponential time hypothesis (SETH) hardness of problems, and the connections to circuit complexity and other aspects of computing.

false

Fall

Undergraduate

3-0-9

6.1200, 6.1210, and (6.1220, 6.1400, or 18.404)

null

false

False

6.5210[J]

Advanced Algorithms

First-year graduate subject in algorithms. Emphasizes fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Surveys a variety of computational models and the algorithms for them. Data structures, network flows, linear programming, computational geometry, approximation algorithms, online algorithms, parallel algorithms, external memory, streaming algorithms.

true

Fall

Graduate

5-0-7

6.1220 and (6.1200, 6.3700, or 18.600)

18.415[J]

false

False

6.5220[J]

Randomized Algorithms

Studies how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Models of randomized computation. Data structures: hash tables, and skip lists. Graph algorithms: minimum spanning trees, shortest paths, and minimum cuts. Geometric algorithms: convex hulls, linear programming in fixed or arbitrary dimension. Approximate counting; parallel algorithms; online algorithms; derandomization techniques; and tools for probabilistic analysis of algorithms.

true

Fall

Graduate

5-0-7

(6.1200 or 6.3700) and (6.1220 or 6.5210)

18.416[J]

false

False

6.5230

Advanced Data Structures

More advanced and powerful data structures for answering several queries on the same data. Such structures are crucial in particular for designing efficient algorithms. Dictionaries; hashing; search trees. Self-adjusting data structures; linear search; splay trees; dynamic optimality. Integer data structures; word RAM. Predecessor problem; van Emde Boas priority queues; y-fast trees; fusion trees. Lower bounds; cell-probe model; round elimination. Dynamic graphs; link-cut trees; dynamic connectivity. Strings; text indexing; suffix arrays; suffix trees. Static data structures; compact arrays; rank and select. Succinct data structures; tree encodings; implicit data structures. External-memory and cache-oblivious data structures; B-trees; buffer trees; tree layout; ordered-file maintenance. Temporal data structures; persistence; retroactivity.

true

Spring

Graduate

3-0-9

6.1220

null

false

False

6.5240

Sublinear Time Algorithms

Sublinear time algorithms understand parameters and properties of input data after viewing only a minuscule fraction of it. Tools from number theory, combinatorics, linear algebra, optimization theory, distributed algorithms, statistics, and probability are covered. Topics include: testing and estimating properties of distributions, functions, graphs, strings, point sets, and various combinatorial objects.

false

Fall

Graduate

3-0-9

6.1220 or permission of instructor

null

false

False

6.5250[J]

Distributed Algorithms

Design and analysis of algorithms, emphasizing those suitable for use in distributed networks. Covers various topics including distributed graph algorithms, locality constraints, bandwidth limitations and communication complexity, process synchronization, allocation of computational resources, fault tolerance, and asynchrony. No background in distributed systems required.

true

Spring

Graduate

3-0-9

6.1220

18.437[J]

false

False

6.5310

Geometric Folding Algorithms: Linkages, Origami, Polyhedra

Covers discrete geometry and algorithms underlying the reconfiguration of foldable structures, with applications to robotics, manufacturing, and biology. Linkages made from one-dimensional rods connected by hinges: constructing polynomial curves, characterizing rigidity, characterizing unfoldable versus locked, protein folding. Folding two-dimensional paper (origami): characterizing flat foldability, algorithmic origami design, one-cut magic trick. Unfolding and folding three-dimensional polyhedra: edge unfolding, vertex unfolding, gluings, Alexandrov's Theorem, hinged dissections.

true

Spring

Graduate

3-0-9

6.1220 or permission of instructor

null

false

False

6.5320

Geometric Computing

Introduction to the design and analysis of algorithms for geometric problems, in low- and high-dimensional spaces. Algorithms: convex hulls, polygon triangulation, Delaunay triangulation, motion planning, pattern matching. Geometric data structures: point location, Voronoi diagrams, Binary Space Partitions. Geometric problems in higher dimensions: linear programming, closest pair problems. High-dimensional nearest neighbor search and low-distortion embeddings between metric spaces. Geometric algorithms for massive data sets: external memory and streaming algorithms. Geometric optimization.

true

Spring

Graduate

3-0-9

6.1220

null

false

False

6.5340

Topics in Algorithmic Game Theory

Presents research topics at the interface of computer science and game theory, with an emphasis on algorithms and computational complexity. Explores the types of game-theoretic tools that are applicable to computer systems, the loss in system performance due to the conflicts of interest of users and administrators, and the design of systems whose performance is robust with respect to conflicts of interest inside the system. Algorithmic focus is on algorithms for equilibria, the complexity of equilibria and fixed points, algorithmic tools in mechanism design, learning in games, and the price of anarchy.

true

Spring

Graduate

3-0-9

6.1210 or 6.1220

null

false

False

6.5350

Matrix Multiplication and Graph Algorithms

Explores topics around matrix multiplication (MM) and its use in the design of graph algorithms. Focuses on problems such as transitive closure, shortest paths, graph matching, and other classical graph problems. Explores fast approximation algorithms when MM techniques are too expensive.

false

Spring

Graduate

3-0-9

6.1220

null

false

False

6.5400[J]

Theory of Computation

A more extensive and theoretical treatment of the material in 6.1400J/18.400J, emphasizing computability and computational complexity theory. Regular and context-free languages. Decidable and undecidable problems, reducibility, recursive function theory. Time and space measures on computation, completeness, hierarchy theorems, inherently complex problems, oracles, probabilistic computation, and interactive proof systems. Students in Course 18 must register for the undergraduate version, 18.404.

true

Fall

Graduate

4-0-8

6.1200 or 18.200

18.4041[J]

false

False

6.5410[J]

Advanced Complexity Theory

Current research topics in computational complexity theory. Nondeterministic, alternating, probabilistic, and parallel computation models. Boolean circuits. Complexity classes and complete sets. The polynomial-time hierarchy. Interactive proof systems. Relativization. Definitions of randomness. Pseudo-randomness and derandomizations. Interactive proof systems and probabilistically checkable proofs.

true

Spring

Graduate

3-0-9

18.404

18.405[J]

false

False

6.5420

Randomness and Computation

The power and sources of randomness in computation. Connections and applications to computational complexity, computational learning theory, cryptography and combinatorics. Topics include: probabilistic proofs, uniform generation and approximate counting, Fourier analysis of Boolean functions, computational learning theory, expander graphs, pseudorandom generators, derandomization.

true

Spring

Graduate

3-0-9

6.1220 and 18.4041

null

false

False

6.5430

Quantum Complexity Theory

Introduction to quantum computational complexity theory, the study of the fundamental capabilities and limitations of quantum computers. Topics include complexity classes, lower bounds, communication complexity, proofs and advice, and interactive proof systems in the quantum world; classical simulation of quantum circuits. The objective is to bring students to the research frontier.

true

Spring

Graduate

3-0-9

6.1400, 18.4041, and 18.435

null

false

False

6.1600

Foundations of Computer Security

Fundamental notions and big ideas for achieving security in computer systems. Topics include cryptographic foundations (pseudorandomness, collision-resistant hash functions, authentication codes, signatures, authenticated encryption, public-key encryption), systems ideas (isolation, non-interference, authentication, access control, delegation, trust), and implementation techniques (privilege separation, fuzzing, symbolic execution, runtime defenses, side-channel attacks). Case studies of how these ideas are realized in deployed systems. Lab assignments apply ideas from lectures to learn how to build secure systems and how they can be attacked.

true

Fall

Undergraduate

4-0-8

(6.1210 and (6.1800 or 6.1810)) or permission of instructor

null

false

False

6.5610

Applied Cryptography

Covers advanced applications of cryptography, implementation of cryptographic primitives, and cryptanalysis. Topics may include: proof systems; zero knowledge; secret sharing; multiparty computation; fully homomorphic encryption; electronic voting; design of block ciphers and hash functions; elliptic-curve and lattice-based cryptosystems; and algorithms for collision-finding, discrete-log, and factoring. Assignments include a final group project. Topics may vary from year to year.

true

Spring

Graduate

4-0-8

6.1200 and (6.1800 or 6.1810)

null

false

False

6.5620[J]

Foundations of Cryptography

A rigorous introduction to modern cryptography. Emphasis on the fundamental cryptographic primitives such as public-key encryption, digital signatures, and pseudo-random number generation, as well as advanced cryptographic primitives such as zero-knowledge proofs, homomorphic encryption, and secure multiparty computation.

true

Fall

Graduate

3-0-9

6.1220, 6.1400, or 18.4041

18.425[J]

false

False

6.5630

Advanced Topics in Cryptography

In-depth exploration of recent results in cryptography.

true

Fall

Graduate

3-0-9

6.5620

null

false

False

6.5660

Computer Systems Security

Design and implementation of secure computer systems. Lectures cover attacks that compromise security as well as techniques for achieving security, based on recent research papers. Topics include operating system security, privilege separation, capabilities, language-based security, cryptographic network protocols, trusted hardware, and security in web applications and mobile phones. Labs involve implementing and compromising a web application that sandboxes arbitrary code, and a group final project.

true

Spring

Graduate

3-6-3

6.1020 and (6.1800 or 6.1810)

null

false

False

6.1800

Computer Systems Engineering

Topics on the engineering of computer software and hardware systems: techniques for controlling complexity; strong modularity using client-server design, operating systems; performance, networks; naming; security and privacy; fault-tolerant systems, atomicity and coordination of concurrent activities, and recovery; impact of computer systems on society. Case studies of working systems and readings from the current literature provide comparisons and contrasts. Includes a single, semester-long design project. Students engage in extensive written communication exercises. Enrollment may be limited.

true

Spring

Undergraduate

5-1-6

6.1910

null

false

False

6.1810

Operating System Engineering

Design and implementation of operating systems, and their use as a foundation for systems programming. Topics include virtual memory, file systems, threads, context switches, kernels, interrupts, system calls, interprocess communication, coordination, and interaction between software and hardware. A multi-processor operating system for RISC-V, xv6, is used to illustrate these topics. Individual laboratory assignments involve extending the xv6 operating system, for example to support sophisticated virtual memory features and networking.

true

Fall

Undergraduate

3-0-9

6.1910

null

false

False