AI Series · Cohort 3
Building Safe, Reliable AI Systems
For developers and engineers who build AI into products and operations: how to design, test, secure and run AI systems that hold up in production.
Next dates to be announced soon
- Possible location
Cities marked with a question mark are under consideration.
Who should attend
- Software developers and engineers
- Data scientists and machine learning engineers
- Solution architects and technical leads
- IT and operational technology teams integrating AI
What participants leave with
- Choose the right approach for a use case: rules, machine learning, large language models or agents
- Build retrieval-based and agent-based applications on your organisation’s own data
- Evaluate AI systems with test sets, metrics and red-teaming before release
- Add guardrails, human approval steps and failsafes to AI-driven workflows
- Secure AI systems against prompt injection, data leakage and misuse
- Deploy, monitor and maintain AI in production, including drift and running costs
Modules
- 01AI system design and architecture
- 02Working with large language models and agents
- 03Retrieval and data pipelines
- 04Evaluation, testing and red-teaming
- 05Security, privacy and guardrails
- 06Deployment, monitoring and operations
Format
Five days, hands-on and lab-based. Participants build, test and harden a working AI application on realistic data, and leave with code and patterns they can reuse.
Leading faculty
Every cohort is led by members of our international faculty: practitioners and academics in leadership, risk, finance, energy economics and technology.