Before diving into machine learning, you’ll want to nail down core Python (data types, control flow and functions), data handling and analysis (Pandas, NumPy), interactive tools (Jupyter, VS Code), solid software engineering practices, and (optionally) the math that powers many algorithms. From there the roadmap walks you through machine learning foundations, deep learning essentials, real-world ML workflows, a bonus section on LLMs, and tips for building killer projects and portfolios.
Looking for resources? Grab a 25% discount on DataCamp’s Python Data Fundamentals Track or ML Scientist with Python Track, or jump into DevLaunch’s mentorship program for hands-on projects, real accountability, and job-ready strategies.
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