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CV

Computer Vision

Promise

Teach machines to see — from image classification to real-time systems.

Courses and prices

  • Computer Vision · Levels 100–200

    16 modules · levels 100–200

    estimated price0 of 16 modules published

  • Computer Vision · Complete · Levels 100–400

    28 modules · levels 100–400

    estimated price0 of 28 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.

100Beginner32h

Modules of this track

  • CV-101Syllabus published

    Images as data (pixels, channels, OpenCV)

    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-106Your first ML model
  • CORE-107Ethics, bias and safety in AI
  • CORE-108Git, GitHub and your portfolio

200Intermediate48h

Modules of this track

  • CV-201Syllabus published

    Classification and augmentation

    Detailed syllabus not written yet

  • CV-202Syllabus published

    Object detection (YOLO)

    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
  • DL-201CNNs (shared with Computer Vision)
  • DL-203Regularisation and normalisation

300Advanced56h

Modules of this track

  • CV-301Syllabus published

    Segmentation

    Detailed syllabus not written yet

  • CV-302Syllabus published

    Vision Transformers and multimodal models (shared with NLP)

    Detailed syllabus not written yet

  • CV-303Syllabus published

    Video and real time

    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
  • DL-301Generative models (VAEs, GANs, diffusion — shared with Vision)

400Expert44h

Modules of this track

  • CV-401Syllabus published

    Edge deployment and optimisation (ONNX, quantisation)

    Detailed syllabus not written yet

  • EX-CVSyllabus published

    Project — a complete vision system

    Content
    Camera + detection + alerting, in production

Reused modules

Comes from elsewhere in the curriculum

  • CORE-304Evaluating AI systems
  • MLOPS-301Observability and monitoring
  • MLOPS-302Serving at scale (batching, caching, autoscaling)