All programmes

Learn to build, deploy and support customer-facing AI systems as an enterprise AI engineer.

A role-aware transition plan that turns your current engineering or data experience into credible AI work.

Ship AI features inside real products: LLM APIs, agents, evals and production patterns.

A Python course built for engineers who need to read, write and ship AI and data code.

Work across OpenAI, Anthropic, Gemini and open-source APIs with provider abstraction, context, reliability and evaluation.

Treat prompting as engineering through reasoning patterns, structured outputs, evaluation, regression testing and versioning.

Cover RAG foundations, embeddings, chunking, vector databases, retrieval, reranking, routing and evaluation.

Study agents that plan, use tools and handle multi-step work through memory, orchestration, safety and control.

Cover MCP protocol design, servers, clients, resources, tools, prompts, authentication and custom transports.

Study agent-to-agent communication through capability discovery, task lifecycle, orchestration and MCP integration.

Cover fine-tuning decisions, dataset preparation, LoRA and QLoRA, training, evaluation, serving and production pipelines.

Cover experiment tracking, feature pipelines, model registry, ML delivery, scalable serving, monitoring and controlled releases.

Move from data analysis to predictive modelling, ML pipelines and model deployment.

Turn raw data into decisions: SQL, Power BI, dashboards and business storytelling.

Build modern web products with React, Node.js, Next.js and system-design fundamentals.

Study architecture decisions across patterns, distributed systems, event-driven design, resilience, scaling and operations.

Cover App Router, rendering, server and client components, caching, route handlers, server actions, performance and SEO.

Cover JavaScript foundations, React hooks and patterns, state, TypeScript, performance, testing, architecture and deployment.

Cover GraphQL schemas, server setup, database integration, access control, performance, frontend use, testing and deployment.

Cover Spring Boot services, discovery, gateways, JWT, Kafka, resilience, configuration, tracing and Kubernetes deployment.

Cover MongoDB CRUD, querying, data modeling, indexes, aggregation, Mongoose, transactions, security, scaling and Atlas.

Deploy, monitor and scale systems on AWS with Docker, Kubernetes and CI/CD.

Learn to monitor, search and alert on machine data with Splunk and modern observability stacks.

Cover containers, Dockerfiles, optimised builds, networking, volumes, Compose, security, registries and CI/CD.

Cover Kubernetes architecture, workloads, networking, storage, RBAC, Helm, autoscaling, observability and GitOps.

Move from manual testing to automation with Selenium, Playwright, API testing and CI/CD.

Build browser automation around WebDriver, locators, synchronisation, framework structure, reporting and CI/CD.

Cover Playwright locators, auto-waiting, API testing, authentication state, visual checks, parallelism and CI/CD.

Cover BDD principles, Gherkin, Cucumber with Java, step definitions, data-driven testing and delivery integrations.

AI literacy for engineering managers, product leads and delivery heads making build-vs-buy decisions.