Training pathways
Choose the engineering path that fits your ambition.
Six specialisations, one shared way of working. Every pathway combines hands-on learning with real engineering activities inside a team.
01
AI Engineering
Building intelligent applications, integrating AI models and developing AI-powered services.
Technologies you may use
- Python
- TypeScript
- AI model APIs
- Vector databases
- REST APIs
What you'll learn
- How large language models and other AI models are used in applications
- Prompt design, retrieval and grounding techniques
- Evaluating and improving the quality of AI outputs
- Building safe, reliable AI-powered features
Practical engineering activities
- Integrate an AI model into a working application
- Design and test prompts against real requirements
- Write evaluations to measure response quality
Example assignments
- Add a natural-language product search to an online shop
- Build an assistant that answers questions from a set of documents
Relevant career opportunities
- AI Engineer
- Machine Learning Engineer
- Software Engineer (AI)
02
AI Platform Engineering
Understanding the infrastructure and engineering systems required to deploy, manage and operate AI applications.
Technologies you may use
- Docker
- Kubernetes concepts
- Cloud AI services
- Terraform
- Monitoring tools
What you'll learn
- How AI workloads are deployed and served
- Managing cost, latency and reliability for AI services
- Securing access to models and data
- Observability for AI-powered systems
Practical engineering activities
- Containerise and deploy an AI service
- Set up logging and metrics for model usage
- Automate the release of AI application updates
Example assignments
- Deploy an AI assistant behind an API with usage monitoring
- Create a pipeline that tests and releases a new model configuration
Relevant career opportunities
- AI Platform Engineer
- MLOps Engineer
- Cloud Engineer
03
Cloud Engineering
Learning how cloud infrastructure supports modern applications and enterprise platforms.
Technologies you may use
- AWS, Azure or Google Cloud
- Terraform
- Linux
- Networking fundamentals
What you'll learn
- Core cloud services for compute, storage, networking and databases
- Designing secure, scalable environments
- Infrastructure as code
- Managing cloud costs
Practical engineering activities
- Provision environments using infrastructure as code
- Configure networking and access controls
- Deploy and scale an application in the cloud
Example assignments
- Build a staging and production environment for a web application
- Review an environment and recommend cost and security improvements
Relevant career opportunities
- Cloud Engineer
- Cloud Support Engineer
- Infrastructure Engineer
04
DevOps and CI/CD
Developing skills in automation, source control, deployment pipelines and infrastructure delivery.
Technologies you may use
- Git and GitHub
- GitHub Actions
- Docker
- Terraform
- Shell scripting
What you'll learn
- Source control workflows and branching strategies
- Building automated test and deployment pipelines
- Containers and repeatable environments
- Release practices that reduce risk
Practical engineering activities
- Create CI pipelines that run tests on every change
- Automate deployments to multiple environments
- Manage secrets and configuration safely
Example assignments
- Set up a pipeline that tests, builds and deploys an application
- Introduce automated checks that block failing changes
Relevant career opportunities
- DevOps Engineer
- Build and Release Engineer
- Automation Engineer
05
Software Engineering
Building maintainable applications using professional engineering practices.
Technologies you may use
- TypeScript or Python
- React and Next.js
- SQL databases
- REST APIs
- Automated testing tools
What you'll learn
- Turning requirements into well-structured code
- Testing, code review and refactoring
- Designing APIs and working with databases
- Writing clear technical documentation
Practical engineering activities
- Deliver features from a sprint backlog
- Review pull requests and act on feedback
- Write unit and integration tests
Example assignments
- Build a product catalogue and ordering API
- Add a new feature to an existing codebase without breaking it
Relevant career opportunities
- Software Engineer
- Full-Stack Developer
- Backend or Frontend Developer
06
Platform Engineering and SRE
Understanding internal platforms, reliability, monitoring, operational excellence and production systems.
Technologies you may use
- Linux
- Containers
- Monitoring and logging tools
- Infrastructure as code
- Incident tooling
What you'll learn
- How internal platforms help engineering teams move faster
- Service levels, reliability targets and error budgets
- Monitoring, alerting and incident response
- Learning from incidents through post-incident reviews
Practical engineering activities
- Define and track reliability targets for a service
- Build dashboards and alerts
- Take part in simulated incident response
Example assignments
- Create a self-service template for deploying new services
- Investigate a simulated outage and write the post-incident review
Relevant career opportunities
- Site Reliability Engineer
- Platform Engineer
- Operations Engineer
Technologies listed are examples and may vary by project. Programme length and any certification arrangements will be confirmed separately.
Not sure which pathway is right for you?
Tell us about your background and goals when you apply, and we'll discuss the pathway that fits you best.