A comprehensive introduction to Python programming, covering functions, variables, control flow, exceptions, libraries, unit testing, file I/O, and object-oriented programming.
Taught by Professor David J. Malan, Harvard CS50P is a rigorous, beginner-accessible university course dedicated entirely to the Python language. Through ten weeks of lectures and hands-on problem sets, learners build fluency in writing clean functions, handling runtime exceptions, testing code with pytest, manipulating files, using regular expressions, and designing object-oriented classes—the exact software engineering habits needed before tackling machine learning algorithms.
Course status is tracked independently from roadmap topic checkboxes so you can mark external courses without altering your topic mastery percentage.
Phase 0 Primary Starting Course (Modules 0.1, 0.2 & 0.4)
All video lectures, course notes, slides, source code, and problem sets are 100% free and openly accessible on Harvard's OpenCourseWare site.
Certificate Note: Harvard CS50 offers a free certificate upon completing required problem sets via CS50.me; verified edX certificates are optional and paid.
Status: Verified (2026-11-09)
Review these foundations before starting so you get the most out of this material:
In Phase 0: Programming Foundations
Start here for Phase 0. Complete Weeks 0–8 and solve the programming problem sets to build rock-solid Python syntax, debugging, pytest unit testing, and object-oriented design fluency.
Core syntax, data structures, object-oriented abstractions, functional generators, and testing discipline in modern Python.
How Python represents objects in memory, reference semantics, mutability pitfalls, and algorithmic complexity.
Tabular data manipulation with Pandas, scientific plotting with Matplotlib, version control with Git, and reproducible Python environments.
Beginner-friendly Python instruction covering programming fundamentals, data structures, files, web data, and databases.
Learn numerical arrays, broadcasting, vectorized computation, matrix operations, and scientific Python fundamentals.
University course exploring the foundational concepts and algorithms of modern artificial intelligence, including search, optimization, machine learning, neural networks, and natural language processing.