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Learn ML end-to-end: regression, classification, model evaluation and the real-world workflow.
Haithem Mihoubi
Instructor
Free course
Enroll instantly — all lessons included
This course includes:
This course builds a correct, practical understanding of machine learning: what a model actually is, supervised learning (regression and classification), how to evaluate models honestly, and the pitfalls (like overfitting) that trip up beginners.
Developers comfortable with Python (see Python for AI & Data) who want a real, non-hand-wavy foundation in ML before diving into deep learning or LLMs.
Full course walkthrough: Machine Learning for everybody
What machine learning actually is
Classification & decision boundaries
Train/test splits & honest evaluation
Overfitting, underfitting & the ML workflow
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