Programme outline
Learning objectives
By the end of course, participants will:
- Build full-stack features using Artificial Intelligence (AI)-native Integrated Development Environments (IDEs).
- Automate terminal-based debugging with Command-line Interface (CLI)-native agents.
- Link AI models to local data via Model Context Protocol (MCP) servers.
- Orchestrate multi-agent workflows using orchestration frameworks.
- Implement codebase Retrieval-Augmented Generation (RAG) for intelligent project navigation.
- Deploy self-healing AI agents within Continuous Integration/Continuous Delivery or Deployment (CI/CD) pipelines.
- Build low-code workflows to automate business-dev operations.
- Modernise legacy systems using autonomous refactoring agents.
- Audit AI-generated code for security and architectural integrity.
- Enforce Application Programming Interfaces (API) contracts through automated AI auditing tools.
Day 1
- Vibe Coding & The AI-First IDE
- The Agentic CLI & Claude Code
- Model Context Protocol (MCP)
- Custom Coding Agents for Scaffolding
Day 2
- RAG for Codebase Intelligence
- Autonomous CI/CD & Self-Healing Pipelines
- Low-Code Automation
- Legacy Modernisation & Contract Enforcement
- Assessment and feedback
Assessment
- Online assessment: 20 MCQs and 2 open-ended questions