Python ML prep starts with rock-solid Python: loops, functions, OOP and data wrangling (think pandas & NumPy). Play around in Jupyter or VS Code, get comfy with Git and Docker, and dust off the optional math to build a strong foundation.
Next up, tackle core ML concepts, level up to deep learning, learn real-world model deployment, and even experiment with LLMs. Round it off with portfolio projects to showcase your skills. For extra support, grab the recommended Datacamp tracks (with a discount!) or join Tim’s DevLaunch mentorship for hands-on guidance.
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