Python Skills You NEED Before Machine Learning

Thinking of diving into ML? You gotta nail the basics first: core Python (syntax, functions, OOP), data wrangling with pandas/numpy, and interactive tools like Jupyter notebooks. Don’t skip software-engineering essentials—Git, debugging, testing—and if you’re feeling brave, revisit your math (stats, linear algebra) to give your code some extra muscle.

Once that foundation’s set, you’ll explore machine-learning fundamentals, toy with deep learning, tackle real-world ML projects, and even peek at LLMs as a bonus. By the end, you’ll have projects for your portfolio and a clear path from beginner tutorials to job-ready expertise.

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