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• Book Cover
• About the Author

1. Preliminaries
2. Programming Basics
3. Decisions
4. Repetition (a.k.a. Loops)
5. Data Structures
6. Functions
7. Libraries
8. Files
9. Object-Oriented Programming (OOP)
10. Data & Datasets
11. Data Analytics
    1. Data Analytics Concepts
    2. Understanding Data Types in the Humanities
    3. Descriptive Analytics
    4. Inferential Analytics
    5. Comparitive Analytics
    6. Advanced Techniques
    7. Tools for Data Analytics
    8. Case Studies
    9. Challenges
    10. Example Project
        • Python Environment Setup
        • Data Analytics in Python
12. Data Visualization
13. Network Analysis
14. Web Scraping
15. Text Analysis
16. Machine Learning (ML)
17. Natural Language Processing (NLP)
18. Neural Networks (NN)
19. Large Language Models (LLMs)
20. Data Science
21. Artificial Intelligence (AI)
22. Geospatial Analysis

• Reference Materials