Masterclass & Best Practices in Generative AI & Large Language Models

Course Introduction

Designed for professionals in Artificial Intelligence & Data Science, this five-day masterclass-style course builds practical command of Generative AI & Large Language Models. Every session pairs a clear concept with a workplace exercise, so learning turns into capability rather than notes.

Training Objectives

• 01Build a shared vocabulary and framework for Generative AI & Large Language Models that your whole team can use
• 02Apply proven methods for Generative AI & Large Language Models to realistic scenarios drawn from data, analytics and automation initiatives
• 03Anticipate the failure points and compliance issues that most often affect Generative AI & Large Language Models
• 04Communicate Generative AI & Large Language Models decisions clearly to colleagues, clients and management
• 05Prepare a personal action plan to apply Generative AI & Large Language Models in your own organisation

What You Will Take Away

• Hands-on lab exercises with guided walkthroughs
• A practical architecture or workflow blueprint
• A risk and controls checklist for your environment

Who Should Attend

• Business & Digital Transformation Leaders
• Data & Analytics Professionals
• IT & Innovation Managers
• Operations Managers Exploring AI

Prerequisites: Best suited to experienced practitioners and team leaders.

Training Methodology

Run as a senior-practitioner masterclass, the programme centres on expert-led discussion, peer exchange and deep analysis of complex situations. Case material and examples are drawn from data, analytics and automation initiatives.

Day-by-Day Programme (5 Days)

• Day 1
  Getting oriented: the landscape of Generative AI & Large Language Models

  Scope, terminology and the standards and regulations that shape Generative AI & Large Language Models in data, analytics and automation initiatives.

• Day 2
  Core concepts and methods

  The principles, codes and best-practice approaches that leading organisations rely on for Generative AI & Large Language Models.

• Day 3
  Applying it on the job

  Hands-on exercises using tools and templates for Generative AI & Large Language Models, built around realistic situations in data, analytics and automation initiatives.

• Day 4
  Cases, risks and lessons learned

  Case studies, typical pitfalls and the risk and compliance issues that arise with Generative AI & Large Language Models.

• Day 5
  Bringing it together

  Consolidation workshop, personal action planning and a closing knowledge check on Generative AI & Large Language Models.

Upcoming Sessions