1. Introduction
2. Courses
3. How to Read
4. Requirements
5. 1. Part I: Foundation
6. 1. 1.1. Linux & Shell Fundamentals
   2. 1. 1.1.1. Unix Philosophy & Command Line
      2. 1.1.2. File System & Permissions
      3. 1.1.3. Process Management
      4. 1.1.4. Text Processing Tools
      5. 1.1.5. Shell Scripting Basics
   3. 1.2. Development Environment with Nix
   4. 1. 1.2.1. Programming Paradigms
      2. 1.2.2. Functional Programming
      3. 1.2.3. Attribute Sets
      4. 1.2.4. Nix Basics
      5. 1.2.5. Nix Core Concepts
   5. 1.3. Version Control with Git
   6. 1. 1.3.1. Git Fundamentals and Workflow
      2. 1.3.2. Repository Management
      3. 1.3.3. Branching and Merging
      4. 1.3.4. Remote Collaboration
      5. 1.3.5. Advanced Git and Troubleshooting
   7. 1.4. Security & Cryptography
   8. 1. 1.4.1. Cryptography Fundamentals
      2. 1.4.2. SSH Key Management
      3. 1.4.3. GPG Data Encryption
      4. 1.4.4. Age Secret Management
      5. 1.4.5. Research Data Security
9. 2. Part II: Scientific Computing
10. 1. 2.1. Python for Science
    2. 1. 2.1.1. Python Ecosystem
       2. 2.1.2. NumPy Arrays
       3. 2.1.3. Pandas Dataframes
       4. 2.1.4. Visualization
       5. 2.1.5. Jupyter Notebooks
    3. 2.2. Data Science
    4. 1. 2.2.1. Exploratory Analysis
       2. 2.2.2. Statistical Testing
       3. 2.2.3. Data Preprocessing
       4. 2.2.4. Dimensionality & Clustering
       5. 2.2.5. Insight Visualization
    5. 2.3. Machine Learning
    6. 1. 2.3.1. Supervised Learning
       2. 2.3.2. Unsupervised Learning
       3. 2.3.3. Model Evaluation
       4. 2.3.4. Hyperparameter Tuning
       5. 2.3.5. scikit-learn Practice
13. 3. Part III: Bioinformatics
14. 1. 3.1. Biological Data Formats
    2. 1. 3.1.1. Sequence Formats
       2. 3.1.2. Structure Formats
       3. 3.1.3. Annotation Formats
       4. 3.1.4. Experimental Data
    3. 3.2. Sequence Analysis
    4. 1. 3.2.1. BioPython
       2. 3.2.2. Alignment Algorithms
       3. 3.2.3. BLAST & Database
       4. 3.2.4. Multiple Alignment
       5. 3.2.5. Motif Discovery
    5. 3.3. Genomics & Transcriptomics
    6. 1. 3.3.1. Genome Assembly
       2. 3.3.2. RNA-seq Pipeline
       3. 3.3.3. Differential Expression
       4. 3.3.4. Functional Enrichment
       5. 3.3.5. scRNA-seq
    7. 3.4. Synthetic Biology
    8. 1. 3.4.1. Circuit Design
       2. 3.4.2. DNA Assembly
       3. 3.4.3. Codon Optimization
       4. 3.4.4. Metabolic Analysis
       5. 3.4.5. SBOL & Automation
    9. 3.5. Evolutionary Engineering
    10. 1. 3.5.1. Simulation
        2. 3.5.2. Adaptive Evolution
        3. 3.5.3. Genetic Diversity
        4. 3.5.4. Selection Pressure
        5. 3.5.5. Trajectory Prediction
17. 4. Part IV: Advanced Applications
18. 1. 4.1. Research Workflows
    2. 1. 4.1.1. Project Structure
       2. 4.1.2. Data Management
       3. 4.1.3. Reproducible Pipelines
       4. 4.1.4. Documentation & Reporting
    3. 4.2. High Performance Computing
    4. 1. 4.2.1. Parallel Processing
       2. 4.2.2. Cluster Computing
       3. 4.2.3. Container Workflows
       4. 4.2.4. Cloud Computing
    5. 4.3. CI/CD for Research
    6. 1. 4.3.1. Research Testing
       2. 4.3.2. Pipeline Automation
       3. 4.3.3. Reproducibility Validation
       4. 4.3.4. Environment Deployment
21. 5. Introduction to Flake
22. 6. Introduction to NixOS
23. 7. Introduction to Nix-Darwin
24. 8. Introduction to Home-Manager