Structure & Objectives
The programme is designed around the rhythm of working professionals. Sessions take place on Fridays and Saturdays, with self-paced preparation in between. Each block moves from concept to application.
Core Competencies:
Mathematical Foundations of Generative & Agentic Systems
Develop a rigorous yet intuitive understanding of probabilistic modelling, vector representations, attention mechanisms, and optimisation dynamics underpinning modern GenAI.
Representation, Uncertainty & Decision-Making
Understand how embeddings, similarity measures, and probabilistic reasoning enable machine percep-tion and decision-making under uncertainty in finance, insurance, and risk-sensitive domains.
Architectures for Agentic Systems
Learn how mathematically grounded models are composed into agentic architectures through retrieval, tool use, orchestration, and multi-agent coordination.
Enterprise Integration & Operating Models
Analyse how agentic systems interact with enterprise architecture layers, data platforms, and operating models to deliver measurable business value.
Philosophy of Generative AI and Agency
Rethink the normative elements of GenAI and reframe meaning, language and understanding from a philosophical viewpoint.
Risk, Governance & Responsible Machine Agency
Gain a structured understanding of model risk, uncertainty propagation, security, and governance and how regulatory frameworks such as the EU AI Act translate into trustworthy AI requirements.
Applied Design & Evaluation Skills
Design, assess, and scale GenAI and agentic systems in real organisational contexts, linking quantitative capabilities to business transformation roadmaps.
Learn more about each block and the dates by clicking on the right "+" to enlarge the section.
Format: 3 x 2 Days in class, 4 ECTS
Style: Lecture with interactive exercises
Assignment: Take home group work
Workload: 2-4h per week when sessions are scheduled
Content:
- Probabilistic modelling & uncertainty
- Overview of generative models
- Tokens, embeddings, transformer
- Building the infrastructure: From models to systems, retrieval and agents
Dates (tbc):
- Welcome Day: 16 October 2026
- Session 1 & 2: 30 & 31 October 2026
- Session 3 & 4: 20 & 21 November 2026
- Session 5: 28 November 2026
- Session 6 & 7: 7 & 8 January 2027
Format: 3 x 2 Days in class (Fri & Sat), 6 ECTS
Style: Interactive workshops with guest speakers and hands-on parts
Workload: Self-learning workload 2-3h per week when sessions are scheduled
Assigment: Use sandbox code to build agentic systems, selected group work
Contents:
- GenAI Product Innovation
- Cases of GenAI and Agentic Workflows
- Multi-agent orchestration
- Governance and model risk
- Technical guardrails and security
Dates (tbc):
- Session 1: 9 January 2027
- Session 2 & 3: 22 & 23 January 2027
- Session 4 & 5: 5 & 6 February 2027
- Session 6 & 7: 19 & 20 February 2027
Format: 1 x 3 Days in class (Thur, Fri & Sat) 2 ECTS
Style: Lecture and Workshops with interactive cases
Workload: Self-learning workload 2-3h in the week with the sessions.
Content:
- Philosophy of Generative AI: Meaning, Understanding and Normativity
- Responsible AI
- Human-in-the-loop & shared agency
- Governance & safety
- Regulatory landscapes
Dates (tbc):
- Session 1, 2 & 3: 11, 12 & 13 March 2027
Format: Individual Project Work over 6-8 weeks, 3 ECTS
Workload: Overall 30h
Innovation Workshop: One-Day Workshop on Ideation & Growth
Contents
- Spurred on by the learnings achieved through Blocks I-III, your project will be tailored to your interests and career goals. This capstone project enables you to apply your knowledge to real-world challenges, showcasing your ability to drive innovation in your field.
- Develop a prototype
- Transformation and sclaing roadmap
How the sessions work
The programme follows contemporary executive-education principles: theory and practice are interleaved within each session, not separated across them.
- Interactive lectures introduce concepts and frameworks, with live discussion and guided coding so ideas become tangible from the first hour.
- Workshops and industry cases place participants inside real enterprise problems - from product design to model risk - with sandbox code to test, modify and extend.
- Interactive group work and peer review build the muscle of working with, and challenging, agentic systems alongside diverse colleagues.
- Mentoring and coaching during the innovation project translate concepts into a prototype and a transformation roadmap relevant to your own organisation.