TL;DR
This video lays out a no-nonsense Python roadmap for aspiring ML engineers: nail down core syntax (variables, functions, OOP), master data handling with pandas/NumPy, get comfy with interactive notebooks and version control, and—if you’re feeling spicy—brush up on the optional math (linear algebra, stats).
Once your foundations are solid, dive into machine learning basics, level up to deep learning, tackle real-world projects (plus a bonus LLM section), and cap it off by building a standout portfolio. Along the way, you’ll pick up links to two beginner-friendly DataCamp tracks and an invite to DevLaunch’s hands-on mentorship for career-focused support.
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