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DL

Deep Learning

Promise

Truly master neural networks — from the mathematics to training large models.

Courses and prices

  • Deep Learning · Levels 100–200

    16 modules · levels 100–200

    estimated price0 of 16 modules published

  • Deep Learning · Complete · Levels 100–400

    26 modules · levels 100–400

    estimated price0 of 26 modules published

The five tracks cost the same despite differing module counts: the price reflects the competence a track delivers and the integrative project that closes it, not how many modules it lists. The MLOps track has fewer modules because it reuses less, not because it delivers less.

100Beginner36h

Modules of this track

  • DL-101Syllabus published

    Visual intuition for neural networks

    Detailed syllabus not written yet

Reused modules

Comes from elsewhere in the curriculum

  • CORE-101What AI, ML and DL are
  • CORE-102Python for AI
  • CORE-103Essential mathematics I
  • CORE-104Data: collection and cleaning
  • CORE-105Basic statistics and probability
  • CORE-106Your first ML model
  • CORE-107Ethics, bias and safety in AI
  • CORE-108Git, GitHub and your portfolio

200Intermediate42h

Modules of this track

  • DL-201Syllabus published

    CNNs (shared with Computer Vision)

    Detailed syllabus not written yet

  • DL-202Syllabus published

    RNNs and sequences

    Detailed syllabus not written yet

  • DL-203Syllabus published

    Regularisation and normalisation

    Detailed syllabus not written yet

Reused modules

Comes from elsewhere in the curriculum

  • CORE-201Essential mathematics II
  • CORE-202Neural networks from scratch
  • CORE-203PyTorch in practice
  • CORE-204Evaluation and experimentation

300Advanced48h

Modules of this track

  • DL-301Syllabus published

    Generative models (VAEs, GANs, diffusion — shared with Vision)

    Detailed syllabus not written yet

  • DL-302Syllabus published

    Modern architectures and reading papers

    Detailed syllabus not written yet

Reused modules

Comes from elsewhere in the curriculum

  • CORE-301The Transformer architecture
  • CORE-302Fine-tuning and transfer learning
  • CORE-303Training optimisation
  • CORE-304Evaluating AI systems

400Expert38h

Modules of this track

  • DL-401Syllabus published

    Distributed training at scale

    Detailed syllabus not written yet

  • DL-402Syllabus published

    Interpretability

    Detailed syllabus not written yet

  • EX-DLSyllabus published

    Project — train a model from scratch

    Content
    Your own mini-GPT or diffusion model, with a technical report

Reused modules

Comes from elsewhere in the curriculum

  • MLOPS-301Observability and monitoring