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Intermediate syllabus

16 lessons · ~10.7h total · titles and estimated time only — the full lesson content is for active members.

Weekly

  1. Evaluating models beyond accuracy~10 min
  2. Feature engineering exercise~22 min
  3. Fine-tune a small model~25 min
  4. Cross-validation and hyperparameter tuning~26 min
  5. Handling imbalanced datasets~24 min
  6. Convolutional neural networks basics~28 min
  7. Recurrent networks and sequence data~26 min
  8. Transfer learning practice~24 min
  9. Build an embeddings-based search~26 min
  10. Model deployment and monitoring basics~26 min

Monthly

  1. Build an ML API~45 min
  2. RAG mini-project~55 min
  3. Kaggle competition attempt~50 min

Yearly

  1. Production ML project~85 min
  2. Specialize in a subfield~80 min
  3. AI agent project~90 min
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