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app.v2.py
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#!/usr/bin/env python3
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"""
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app.py
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A Streamlit application that displays a densified skill‐tree overview.
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It includes:
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- A Markdown outline (with up to three sub–levels) for nine skill areas.
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- Individual Mermaid diagrams for each area.
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- A combined overall skill tree Mermaid diagram showing inter–area relationships.
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Each node is annotated with between 1 (simplest) to 5 (most complex) emojis.
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"""
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import streamlit as st
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import streamlit.components.v1 as components
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def render_mermaid(mermaid_code, height=500):
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html_code = f"""
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<html>
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<head>
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<script src="https://cdn.jsdelivr.net/npm/mermaid/dist/mermaid.min.js"></script>
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<style>
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body {{
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background-color: white;
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font-family: sans-serif;
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}}
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</style>
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</head>
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<body>
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<div class="mermaid">
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{mermaid_code}
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</div>
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<script>
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mermaid.initialize({{startOnLoad:true}});
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</script>
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</body>
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</html>
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"""
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components.html(html_code, height=height)
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def main():
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st.set_page_config(page_title="Densified Skill Tree", layout="wide")
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st.title("Densified Skill Tree Overview")
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st.markdown("---")
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# Markdown Outline
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st.header("Markdown Outline")
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markdown_outline = r'''
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# Skill Tree Outline
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## 🔧 Systems Infrastructure LowLevel Engineering
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- **Distributed & HPC Deployment (5 🔧’s)**
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- Data–center scale HPC/ML deployment & GPU cluster orchestration.
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- Multi–GPU training pipelines and distributed debugging.
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- **Advanced ML & Automation in Systems (4 🔧’s)**
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- Cross–team innovation and proactive ML–based resolution.
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- Observability, anomaly detection & ServiceNow automation.
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- **Performance & Tuning (3 🔧’s)**
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- Cross–layer tuning, quantitative throughput modeling.
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- Load balancing and performance optimization under heavy ML loads.
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- **Hardware & OS Integration (2 🔧’s)**
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- Linux/embedded systems and low–level integrations (C/C++).
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## 💻 Software Cloud MLOps Infrastructure
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- **Cloud & Infrastructure Provisioning (5 💻’s)**
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- Kubernetes orchestration, Docker containerization & cloud integration (AWS/GCP/Azure).
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- Infrastructure as Code (Terraform, Helm) and production environment management.
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- **ML Frameworks & Automation (4 💻’s)**
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- Python APIs, ML libraries (PyTorch, Keras) & distributed frameworks (Ray, Horovod).
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- Framework optimizations and automated deployments.
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- **Data Pipelines & Processing (3 💻’s)**
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- Distributed data processing with Spark, Airflow & robust ETL pipelines.
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- **Developer Tooling & Observability (2 💻’s)**
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- Full–stack development, debugging tools & reliability scaling (SRE).
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## 🤖 Machine Learning AI Model Development
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- **Large–Scale Architectures & Retrieval (5 🤖’s)**
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- Managing Transformers, retrieval optimization (RAG, vector DBs) & semantic search.
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- **Experimentation & Distributed Training (4 🤖’s)**
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- Experimental design, distributed training, reinforcement learning & quantization.
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- **Application & API Development (3 🤖’s)**
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- Agentic AI, LLM inference, microservices & API construction.
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- **Optimization & Monitoring (2 🤖’s)**
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- Performance tuning, scaling ML services & reliability monitoring.
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## 📊 Data Engineering Analytics Data Governance
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- **Data Processing & Ingestion (5 📊’s)**
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- Multi–modal data processing, large event data handling & ETL pipelines.
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- **Analytics, Forecasting & Visualization (4 📊’s)**
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- Advanced analytics, forecasting, dashboards & BI tool integration.
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- **Data Governance & Quality (3 📊’s)**
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- Data modeling, warehousing, root–cause analysis & stakeholder communications.
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## 🔒 Security Compliance Reliability
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- **Security Operations & Incident Response (5 🔒’s)**
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- Coordinating security teams, incident management, vulnerability assessment & penetration testing.
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- **Compliance & Governance (4 🔒’s)**
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- Data quality standards, compliance policies & IAM solutions.
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- **System Hardening & Automation (3 🔒’s)**
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- Secure HPC/ML pipeline design, Python/Bash automation & cost optimization.
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## 👥 Leadership Management Collaboration
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- **Strategic & Cross–Functional Leadership (5 👥’s)**
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- Global strategy, cross–team coordination, vendor management & project planning.
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- **Team Building & Agile Collaboration (4 👥’s)**
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- Team coaching, agile processes & stakeholder management.
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- **Domain Expertise & Innovation (3 👥’s)**
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- Deep AI framework knowledge, product strategy & cross–disciplinary innovation.
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## 📱 FullStack UI Mobile Product Development
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- **Mobile & Web App Development (5 📱’s)**
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- Full–stack development, CI/CD pipelines, API design & ML–driven product delivery.
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- **UI/UX & Frontend Integration (4 📱’s)**
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- React/Next.js, TypeScript & intuitive, user–centric UI design.
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- **Backend & Cross–Platform Tools (3 📱’s)**
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- Python/Node backends, cloud microservices & bridging ML models to frontends.
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## 🎯 Specialized Domains Emerging Technologies
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- **Advanced CV & 3D Graphics (5 🎯’s)**
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- 3D computer vision, neural rendering, advanced reconstruction & graphics engines.
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- **Robotics, Autonomous Systems & Simulation (4 🎯’s)**
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- Autonomous vehicles, robotics, sensor fusion & path planning.
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- **HPC & Hardware Integration (3 🎯’s)**
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- GPU/SoC modeling, HPC networking, hardware prototyping & programmable networks.
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- **AI Quantization & Inference (2 🎯’s)**
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- Quantization techniques, in–browser inference & neural sparse models.
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## 📢 Community OpenSource Communication
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- **Technical Documentation & Demos (5 📢’s)**
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- Contributing documentation, code examples, demos & technical notebooks.
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- **Community Engagement & Collaboration (4 📢’s)**
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- Public speaking, social media engagement & strategic collaborations.
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'''
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st.markdown(markdown_outline)
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st.markdown("---")
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st.header("Mermaid Graphs by Area")
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# Dictionary mapping area names to their mermaid code strings.
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mermaid_areas = {
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"Systems Infrastructure LowLevel Engineering": r'''
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graph TD
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A[🔧 Systems Infrastructure]
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A --> A1[🔧🔧 Hardware & OS Integration: Linux, embedded, C/C++]
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A --> A2[🔧🔧🔧 Performance & Tuning: Cross–layer tuning, throughput & load balancing]
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A --> A3[🔧🔧🔧🔧 Advanced ML & Automation: Cross–team innovation, observability & ServiceNow]
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A --> A4[🔧🔧🔧🔧🔧 Distributed & HPC Deployment: Data–center HPC/ML, GPU orchestration & multi–GPU pipelines]
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''',
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"Software Cloud MLOps Infrastructure": r'''
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graph TD
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B[💻 Software Cloud MLOps]
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B --> B1[💻💻 Developer Tooling & Observability: Full–stack dev, debugging & SRE]
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B --> B2[💻💻💻💻 ML Frameworks & Automation: Python APIs, PyTorch/Keras & Ray/Horovod]
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B --> B3[💻💻💻 Data Pipelines & Processing: Spark, Airflow & ETL pipelines]
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B --> B4[💻💻💻💻💻 Cloud & Infrastructure Provisioning: Kubernetes, Docker, Terraform & cloud integration]
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''',
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"Machine Learning AI Model Development": r'''
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graph TD
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C[🤖 Machine Learning AI]
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C --> C1[🤖🤖🤖🤖🤖 Large–Scale Architectures & Retrieval: Transformers, RAG & vector DBs]
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C --> C2[🤖🤖🤖🤖 Experimentation & Distributed Training: RL, quantization & ablation studies]
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C --> C3[🤖🤖🤖 Application & API Development: Agentic AI, LLM inference & microservices]
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C --> C4[🤖🤖 Optimization & Monitoring: Performance tuning, scaling & reliability]
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''',
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"Data Engineering Analytics Data Governance": r'''
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graph TD
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D[📊 Data Engineering]
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D --> D1[📊📊📊📊📊 Data Processing & Ingestion: Multi–modal data, event handling & ETL]
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D --> D2[📊📊📊📊 Analytics, Forecasting & Visualization: BI, dashboards & forecasting]
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D --> D3[📊📊📊 Data Governance & Quality: Modeling, warehousing & stakeholder comms]
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''',
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"Security Compliance Reliability": r'''
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graph TD
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E[🔒 Security & Compliance]
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E --> E1[🔒🔒🔒🔒🔒 Security Operations & Incident Response: Incident management, pen testing & vulnerability assessment]
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E --> E2[🔒🔒🔒🔒 Compliance & Governance: Data quality, compliance policies & IAM]
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E --> E3[🔒🔒🔒 System Hardening & Automation: Secure HPC/ML, Python/Bash automation & cost optimization]
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''',
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"Leadership Management Collaboration": r'''
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graph TD
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F[👥 Leadership & Collaboration]
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F --> F1[👥👥👥👥👥 Strategic & Cross–Functional Leadership: Global strategy, team coordination & vendor management]
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F --> F2[👥👥👥👥 Team Building & Agile Collaboration: Coaching, agile processes & stakeholder management]
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F --> F3[👥👥👥 Domain Expertise & Innovation: Deep AI knowledge & product strategy]
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''',
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"FullStack UI Mobile Product Development": r'''
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graph TD
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G[📱 FullStack UI Mobile]
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G --> G1[📱📱📱📱📱 Mobile & Web App Development: Full–stack, CI/CD & API design]
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G --> G2[📱📱📱📱 UI/UX & Frontend Integration: React, Next.js, TypeScript & intuitive design]
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G --> G3[📱📱📱 Backend & Cross–Platform Tools: Python/Node, cloud microservices & ML bridging]
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''',
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"Specialized Domains Emerging Technologies": r'''
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graph TD
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H[🎯 Specialized Domains]
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H --> H1[🎯🎯🎯🎯🎯 Advanced CV & 3D Graphics: Neural rendering, reconstruction & graphics engines]
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H --> H2[🎯🎯🎯🎯 Robotics & Autonomous Systems: Autonomous vehicles, sensor fusion & path planning]
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H --> H3[🎯🎯🎯 HPC & Hardware Integration: GPU/SoC modeling, HPC networking & prototyping]
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H --> H4[🎯🎯 AI Quantization & Inference: Quantization, in–browser inference & neural sparse models]
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''',
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"Community OpenSource Communication": r'''
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graph TD
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I[📢 Community OpenSource]
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I --> I1[📢📢📢📢📢 Technical Documentation & Demos: Code examples, demos & notebooks]
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I --> I2[📢📢📢📢 Community Engagement & Collaboration: Public speaking, social media & collabs]
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'''
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}
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# Render each area with its own subheader and Mermaid diagram.
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for area, mermaid_code in mermaid_areas.items():
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st.subheader(area)
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render_mermaid(mermaid_code, height=300)
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st.markdown("---")
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st.header("Combined Overall Skill Tree Graph")
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combined_mermaid = r'''
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graph TD
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S[🔧 Systems Infrastructure]
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CLO[💻 Software Cloud MLOps]
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ML[🤖 Machine Learning AI]
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DE[📊 Data Engineering]
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SEC[🔒 Security & Compliance]
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LEAD[👥 Leadership & Collaboration]
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UI[📱 FullStack UI Mobile]
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SPEC[🎯 Specialized Domains]
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COMM[📢 Community OpenSource]
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S --> CLO
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CLO --> ML
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ML --> DE
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SEC --- ML
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SEC --- CLO
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LEAD --- S
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LEAD --- ML
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UI --- CLO
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UI --> SPEC
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SPEC --- ML
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LEAD --- SEC
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COMM --- LEAD
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COMM --- DE
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SPEC --- COMM
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'''
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render_mermaid(combined_mermaid, height=400)
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if __name__ == "__main__":
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main()
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