Ready to dive into ML? First, master core Python—think variables, functions, OOP, plus data handling with pandas/NumPy, and essential SWE tools like Git and testing. A math refresher is optional, since you’ll learn most on the job. Then tackle machine learning foundations with scikit-learn, deep learning basics, real-world ML projects and even a taste of LLMs to round out your skill set.
For hands-on practice, check out the Python Data Fundamentals and ML Scientist with Python tracks on DataCamp (grab my 25% off link!), or join DevLaunch for real-world project mentorship. Build killer projects, polish your portfolio, and get the accountability you need to actually land that data science gig!
Watch on YouTube
Top comments (0)