Programming & CS Foundations
How to think like a programmer — from zero, before any AI or math content
8 phases. 31 lessons. 31 labs. 1 capstone. The true zero-background starting point for this entire platform — bits and memory, real Python (variables through classes), the data structures and algorithmic reasoning every later course assumes, testing and code quality, and a self-designed capstone tool. No prior programming or CS background required.
- Lessons: —
- Labs: —
- Projects: —
- Level: Beginner
Curriculum
- How Computers Actually Work — Bits and bytes, RAM vs. disk, the fetch-execute cycle, CPU vs. GPU cores, and classifying syntax vs. runtime vs. logic errors.
- Programming Fundamentals I — Variables and assignment, if/elif/else, for and while loops, functions with parameters and return values, modules and imports.
- Programming Fundamentals II — Lists, tuples, dicts, and sets; string processing; reading and writing files and CSVs; try/except error handling.
- Data & Statistical Literacy — Categorical vs. numerical data, mean/median/mode/standard deviation, distribution shape, correlation vs. causation.
- Computational Thinking & Algorithms — Linear vs. binary search, Big-O reasoning from measured timing, sorting, recursion, and choosing the right data structure.
- Object-Oriented & Modular Thinking — Classes, __init__ and self, the configure-once/reuse-repeatedly pattern behind ML libraries, composition over inheritance.
- Testing & Code Quality — Why 'it ran' isn't 'it's correct,' writing real pytest tests, reading test failures, and linting with ruff.
- Capstone — Designing a real tool before writing code, building incrementally, and shipping a tested, linted, multi-file program.
Skills You Will Learn
- Python Programming
- Data Structures
- Algorithmic Thinking
- Object-Oriented Design
- Automated Testing
- Code Quality
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