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8 programs, 9 subject areas, 6 career directions
Artificial Intelligence
From machine learning foundations to language models, agents and the platforms that run them in production.
Inside a neural network
Signals in, decisions out.
Each layer weighs the signals from the one before it. Training adjusts those weights until the outputs are right. Click the network to send a new input through it; point at a node to read its activation.
An illustration for learning, not a live model.
What this domain covers
Every subject area below is taught inside a full program, not as a thin standalone course. Each area links to the programs that teach it in depth.
AI foundations
Python, mathematics and core concepts every AI practitioner relies on.
Artificial intelligence fundamentals, Python programming for AI, Mathematics for AI, Probability and statistics for AI, Introduction to machine learning, AI literacy for professionals, AI for business leaders, Responsible AI fundamentals
Taught in Machine Learning Engineering and AI & Deep Learning
Machine learning
Models that learn from tabular and structured data.
Machine learning engineering, Supervised learning, Unsupervised learning, Feature engineering, Model evaluation and optimisation, Ensemble learning, Advanced machine learning, Applied ML with Python
Taught in Machine Learning Engineering and Applied Data Science
Deep learning
Neural networks from first principles to modern architectures.
Deep learning fundamentals, Neural network engineering, PyTorch development, TensorFlow and Keras, Convolutional neural networks, Recurrent neural networks, Transformer architectures, Representation learning
Taught in AI & Deep Learning
Generative AI
Building products on large language and multimodal models.
Generative AI foundations, LLM fundamentals, LLM application development, Prompt engineering, Retrieval-augmented generation, Vector databases and embeddings, LLM fine-tuning, Multimodal AI, Synthetic data generation, GenAI product development
Taught in Generative AI Engineering and LLMs & RAG Systems
Agentic AI
Systems that plan, use tools and act, with people in control.
Agentic AI fundamentals, AI agent engineering, Autonomous workflow design, Multi-agent systems, Tool-using agents, Agent orchestration, Agent memory and context, Agent evaluation and observability, Human-in-the-loop systems, Secure agent deployment, Enterprise agentic architecture
Taught in Agentic AI & Autonomous Systems and AI Systems Architecture
Natural language processing
Understanding and generating human language.
NLP fundamentals, Text classification, Information extraction, Semantic search, Language model evaluation, Conversational AI, Speech and language AI
Taught in AI & Deep Learning and LLMs & RAG Systems
Computer vision
Images, video and models that combine vision with language.
Computer vision fundamentals, Image classification, Object detection, Image segmentation, Vision transformers, Video analytics, Vision-language systems
Taught in Computer Vision & Multimodal AI
AI engineering and operations
Running models and AI services reliably in production.
MLOps, LLMOps, Model serving and deployment, AI infrastructure, AI systems architecture, Cloud AI engineering, Model monitoring, AI security, AI reliability engineering, Production RAG systems
Taught in MLOps & AI Deployment and AI Systems Architecture
Specialised AI
Advanced and applied directions, taught as electives and future programs.
Reinforcement learning, Robotics AI foundations, Edge AI, AI for cybersecurity, AI for healthcare, AI for financial analytics, AI product management, AI governance, AI ethics and safety, Explainable AI, Evaluation and red teaming, AI research methods
Taught in AI & Deep Learning and AI Systems Architecture
Pathways that cross domains
Programs are designed to stack. These sequences are common routes; PathFinder will suggest one for your situation.
Data to AI engineering
All artificial intelligence programs
8 programs
Professional Certificate, AI
Generative AI EngineeringBuild, evaluate and ship applications on large language models.
- Length
- 6 or 12 months
- Level
- Intermediate
- Weekly time
- 8 to 12 h/week
- Formats
- Live cohort, Hybrid
Professional Certificate, AI
Machine Learning EngineeringFrom a dataset to a model that runs reliably in production.
- Length
- 6 or 12 months
- Level
- Intermediate
- Weekly time
- 8 to 12 h/week
- Formats
- Live cohort, Hybrid, Self-paced
Professional Certificate, AI
MLOps & AI DeploymentKeep models and LLM services healthy after launch.
- Length
- 3 or 6 months
- Level
- Intermediate
- Weekly time
- 6 to 10 h/week
- Formats
- Live cohort, Self-paced
Advanced Program, AI
Agentic AI & Autonomous SystemsDesign agents that plan, use tools and stay inside the lines.
- Length
- 6 months
- Level
- Advanced
- Weekly time
- 10 to 14 h/week
- Formats
- Live cohort
Professional Certificate, AI
Computer Vision & Multimodal AITeach systems to see, read and describe.
- Length
- 6 months
- Level
- Intermediate
- Weekly time
- 8 to 12 h/week
- Formats
- Live cohort, Hybrid
Advanced Program, AI
LLMs & RAG SystemsRetrieval that is accurate, current and measurable.
- Length
- 3 or 6 months
- Level
- Intermediate
- Weekly time
- 8 to 12 h/week
- Formats
- Live cohort, Hybrid
Advanced Program, AI
AI & Deep LearningThe mathematics, architectures and practice of modern neural networks.
- Length
- 12 or 18 months
- Level
- Advanced
- Weekly time
- 10 to 15 h/week
- Formats
- Live cohort, Hybrid
Advanced Program, AI
AI Systems ArchitectureDesign AI platforms that scale, stay secure and pass review.
- Length
- 12 or 18 months
- Level
- Advanced
- Weekly time
- 8 to 12 h/week
- Formats
- Live cohort
Where this leads
Roles these programs prepare you to work toward. We describe the work; we don't promise jobs or salaries.
AI Engineer
Builds products and internal tools on top of language and multimodal models.
Explore this roleMachine Learning Engineer
Turns data into models and models into dependable services.
Explore this roleMLOps Engineer
Keeps models and AI services healthy in production.
Explore this roleComputer Vision Engineer
Builds systems that interpret images and video.
Explore this roleAI Solutions Architect
Designs how AI capabilities fit into an organisation's systems.
Explore this roleAI Product or Engineering Leader
Sets direction for AI products, platforms and teams.
Explore this role