Precision dialog with AI about textbooks in a folder.

*0:09–1:03:* Overview of 17–18 No Starch Press books (~10,000 pages), covering Python, C++, ML, algorithms, and more. Use Notebook LLM to interact with the entire library, deriving six themes: algorithms, data structures, debugging, best practices, fundamentals, and advanced concepts.

*1:03–15:00:* Examples of linked themes and books: Automate the Boring Stuff for debugging, Learn Python Visually for fundamentals, and Dive into Algorithms for advanced concepts. Highlights data structures (lists, stacks, heaps) and algorithmic thinking (recursion, graph algorithms).

*15:00–30:00:* Insights into debugging, error handling, and API usage with Hacking APIs and Python Crash Course*. Discussion of OOP concepts in *Object-Oriented Python with practical applications like GUI development and games.

*30:00–45:00:* Advanced coding practices from Serious Python and *Dead Simple Python*, focusing on production-ready code, unit testing, scaling, and optimization. Introduction to API interactions and network protocols from *TCP/IP Guide*.

*45:00–1:00:00:* Algorithmic problem-solving applications from Dive into Algorithms and *Think Like a Programmer*. Practical examples include recursive solutions and dynamic programming strategies for real-world problems.

*1:00:00–1:15:00:* Exploration of compact, efficient coding techniques in *Python One-Liners*. Coverage of decorators, functional programming, and scaling software architectures from *Serious Python*.

*1:15:00–1:20:22:* Focus on building a practical project portfolio by leveraging tools and insights from the library. Recommended projects include web scraping, PDF automation, and OOP-based applications. AI tools simplify mapping and optimizing learning paths.