beginner
14 study hoursPython for AI
Use Python, notebooks, NumPy and structured datasets.
Put it into practice
Load, inspect and transform a small public dataset.
All learning paths
Artificial Intelligence
AI & machine learning
Build from Python and mathematics to models, evaluation and responsible AI.
6 recommended milestones~23 weeks · 5 hours / week
Build and evaluate a machine-learning project with a responsible-use report.
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- 01
- 02
beginner
18 study hoursMathematical foundations
Review probability, linear algebra and the intuition behind optimization.
Put it into practice
Explain a matrix transformation and calculate a simple probability model.
- 03
intermediate
18 study hoursMachine-learning fundamentals
Learn supervised learning, train/test splits, overfitting and metrics.
Put it into practice
Train a baseline classifier and report precision and recall.
- 04
intermediate
22 study hoursDeep learning
Explore neural networks, embeddings and practical model training.
Put it into practice
Train a small neural network and compare it with your baseline.
- 05
advanced
16 study hoursGenerative AI & responsible use
Study transformers, retrieval, evaluation, bias and privacy.
Put it into practice
Evaluate an AI application's accuracy, limitations and privacy risks.
- 06
advanced
24 study hoursApplied AI project
Build a reproducible model workflow and communicate its limitations.
Put it into practice
Publish a model evaluation, dataset notes and responsible-use report.