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Full curriculum

The complete module catalogue, with code, syllabus and hands-on exercise wherever the programme already defines them. Area modules are listed by title: their detailed syllabus has not been written yet, and listing one before it exists would misrepresent the stage of the work.

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Syllabus published
Module designed, with a defined place in the curriculum. Not recorded.
Script ready
Script, slides and code repository written.
In production
Video production started.
Available
Available to students.

0 / 63 · 2026-08-05

Shared trunk (CORE)

Recorded once, used across all or nearly all tracks.

100Beginner

  • CORE-101Syllabus published

    What AI, ML and DL are

    Content
    History, types of learning, where AI already is in the real world
    Hands-on
    Map 5 everyday AI systems and classify them

    estimated price0 of 1 module published

  • CORE-102Syllabus published

    Python for AI

    Content
    Syntax, functions, environments (venv/conda), notebooks
    Hands-on
    Mini-project: a simple text analyser

    estimated price0 of 1 module published

  • CORE-103Syllabus published

    Essential mathematics I

    Content
    Vectors, matrices, functions, the idea of a derivative — visual and intuitive
    Hands-on
    Implement the operations with NumPy

    estimated price0 of 1 module published

  • CORE-104Syllabus published

    Data: collection and cleaning

    Content
    Pandas, CSV/JSON/APIs, missing data, EDA
    Hands-on
    Clean and explore a real, messy dataset

    estimated price0 of 1 module published

  • CORE-105Syllabus published

    Basic statistics and probability

    Content
    Distributions, mean/variance, correlation vs. causation
    Hands-on
    Statistical analysis of a public dataset

    estimated price0 of 1 module published

  • CORE-106Syllabus published

    Your first ML model

    Content
    Scikit-learn: regression and classification, train/test split, metrics
    Hands-on
    Predict housing prices + classify spam

    estimated price0 of 1 module published

  • CORE-107Syllabus published

    Ethics, bias and safety in AI

    Content
    Bias in data, privacy, responsible use
    Hands-on
    Audit an off-the-shelf model for bias

    estimated price0 of 1 module published

  • CORE-108Syllabus published

    Git, GitHub and your portfolio

    Content
    Version control, README, publishing projects
    Hands-on
    Push every project from this level to GitHub

    estimated price0 of 1 module published

200Intermediate

  • CORE-201Syllabus published

    Essential mathematics II

    Content
    Gradients, optimisation, applied linear algebra
    Hands-on
    Gradient descent from scratch in NumPy

    estimated price0 of 1 module published

  • CORE-202Syllabus published

    Neural networks from scratch

    Content
    Perceptron, backpropagation, activation functions
    Hands-on
    Implement a neural network with no framework

    estimated price0 of 1 module published

  • CORE-203Syllabus published

    PyTorch in practice

    Content
    Tensors, autograd, training loops, GPU
    Hands-on
    Rewrite the CORE-202 network in PyTorch

    estimated price0 of 1 module published

  • CORE-204Syllabus published

    Evaluation and experimentation

    Content
    Overfitting, cross-validation, experiment tracking (W&B/MLflow)
    Hands-on
    Run and compare 10 experiments

    estimated price0 of 1 module published

  • CORE-205Syllabus published

    AI APIs and prompt engineering

    Content
    OpenAI/Anthropic/OSS, function calling, cost
    Hands-on
    A CLI app that calls an LLM through an API

    estimated price0 of 1 module published

  • CORE-206Syllabus published

    Basic deployment

    Content
    FastAPI, Docker, shipping a model as an API
    Hands-on
    Put the CORE-203 model into production

    estimated price0 of 1 module published

300Advanced

  • CORE-301Syllabus published

    The Transformer architecture

    Content
    Attention, embeddings, positional encoding, encoder/decoder
    Hands-on
    Implement attention from scratch and visualise it

    estimated price0 of 1 module published

  • CORE-302Syllabus published

    Fine-tuning and transfer learning

    Content
    LoRA/QLoRA, layer freezing, datasets
    Hands-on
    Fine-tune an open-source model

    estimated price0 of 1 module published

  • CORE-303Syllabus published

    Training optimisation

    Content
    Mixed precision, schedulers, distributed basics
    Hands-on
    Make a training run 3× faster

    estimated price0 of 1 module published

  • CORE-304Syllabus published

    Evaluating AI systems

    Content
    Benchmarks, LLM evals, A/B testing, red teaming
    Hands-on
    Build an eval suite for an application

    estimated price0 of 1 module published

Area modules

Shared between two or three tracks.

Only CORE trunk modules are sold on their own, because only those have a defined syllabus and exercise in this catalogue. The rest appear with code, level and status, and are acquired inside the track that contains them.

AG

  • AG-101Syllabus published

    What agents are: LLM + tools + loop

    Detailed syllabus not written yet

  • AG-102Syllabus published

    Chatbots vs. agents (hands-on with APIs)

    Detailed syllabus not written yet

  • AG-201Syllabus published

    Function calling and tool use

    Detailed syllabus not written yet

  • AG-202Syllabus published

    Agent memory and state

    Detailed syllabus not written yet

  • AG-203Syllabus published

    Frameworks (LangGraph, CrewAI, agent SDKs)

    Detailed syllabus not written yet

  • AG-301Syllabus published

    Multi-agent systems and orchestration

    Detailed syllabus not written yet

  • AG-302Syllabus published

    Planning, reflection and self-correction

    Detailed syllabus not written yet

  • AG-303Syllabus published

    MCP and integration with real systems

    Detailed syllabus not written yet

  • AG-304Syllabus published

    Agent security (prompt injection, sandboxing)

    Detailed syllabus not written yet

  • AG-401Syllabus published

    Agents in production: cost, latency, observability

    Detailed syllabus not written yet

  • AG-402Syllabus published

    RL for agents (fundamentals)

    Detailed syllabus not written yet

DL

  • DL-101Syllabus published

    Visual intuition for neural networks

    Detailed syllabus not written yet

  • 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

  • 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

  • DL-401Syllabus published

    Distributed training at scale

    Detailed syllabus not written yet

  • DL-402Syllabus published

    Interpretability

    Detailed syllabus not written yet

CV

  • CV-101Syllabus published

    Images as data (pixels, channels, OpenCV)

    Detailed syllabus not written yet

  • CV-201Syllabus published

    Classification and augmentation

    Detailed syllabus not written yet

  • CV-202Syllabus published

    Object detection (YOLO)

    Detailed syllabus not written yet

  • 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

  • CV-401Syllabus published

    Edge deployment and optimisation (ONNX, quantisation)

    Detailed syllabus not written yet

NLP

  • NLP-101Syllabus published

    Text as data (tokens, cleaning, regex)

    Detailed syllabus not written yet

  • NLP-201Syllabus published

    Embeddings and semantic search

    Detailed syllabus not written yet

  • NLP-202Syllabus published

    End-to-end RAG (shared with Agentic AI)

    Detailed syllabus not written yet

  • NLP-203Syllabus published

    Classification and NER

    Detailed syllabus not written yet

  • NLP-301Syllabus published

    Fine-tuning LLMs in practice

    Detailed syllabus not written yet

  • NLP-302Syllabus published

    Alignment (RLHF/DPO — fundamentals)

    Detailed syllabus not written yet

  • NLP-401Syllabus published

    Efficient LLMs (quantisation, inference serving)

    Detailed syllabus not written yet

MLOPS

  • MLOPS-101Syllabus published

    How AI becomes a product (systems view)

    Detailed syllabus not written yet

  • MLOPS-201Syllabus published

    Data pipelines

    Detailed syllabus not written yet

  • MLOPS-202Syllabus published

    CI/CD for ML

    Detailed syllabus not written yet

  • MLOPS-203Syllabus published

    Cloud for AI (GPU, storage, cost)

    Detailed syllabus not written yet

  • MLOPS-301Syllabus published

    Observability and monitoring

    Detailed syllabus not written yet

  • MLOPS-302Syllabus published

    Serving at scale (batching, caching, autoscaling)

    Detailed syllabus not written yet

  • MLOPS-401Syllabus published

    AI platform architecture

    Detailed syllabus not written yet

Integrative projects (EX)

Exclusive to a single track. They close the expert level.

Only CORE trunk modules are sold on their own, because only those have a defined syllabus and exercise in this catalogue. The rest appear with code, level and status, and are acquired inside the track that contains them.

  • EX-AGSyllabus published

    Project — a complete autonomous agent

    Content
    A research-and-execution agent that solves a business task end to end
  • EX-DLSyllabus published

    Project — train a model from scratch

    Content
    Your own mini-GPT or diffusion model, with a technical report
  • EX-CVSyllabus published

    Project — a complete vision system

    Content
    Camera + detection + alerting, in production
  • EX-NLPSyllabus published

    Project — a complete language product

    Content
    A domain-specialised RAG assistant, with evals
  • EX-MLOPSSyllabus published

    Project — a complete platform

    Content
    Pipeline → training → deployment → monitoring, fully automated