TL;DR
This video lays out a complete Python roadmap before you dive into machine learning: start with core Python (control flow, OOP, data structures), then tackle data handling and analysis with NumPy/Pandas, get comfy in interactive environments (Jupyter, VS Code), and nail down essential software-engineering tools (Git, testing). From there you can brush up on optional math, explore ML foundations (scikit-learn), dive into deep learning frameworks, see real-world ML in action, and even touch on LLMs—then pull it all together with portfolio projects.
On the learning-resources front, you get two top Datacamp tracks (Python Data Fundamentals and ML Scientist) with a 25% discount via the exclusive link, plus an invite to join DevLaunch for hands-on mentorship, real project builds, and career guidance to help you actually land that job.
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