Foundation Programme in Generative AI & Large Language Models

Course Introduction

Delivered over five days, this foundation-level programme on Generative AI & Large Language Models combines concise technical input with hands-on application. It is built around data, analytics and automation initiatives, so examples, exercises and discussion stay relevant to participants' daily work.

Training Objectives

• 01Explain the core principles, terminology and standards behind Generative AI & Large Language Models in clear, practical language
• 02Select and adapt suitable approaches to Generative AI & Large Language Models for the constraints of data, analytics and automation initiatives
• 03Diagnose weak spots in current practice and prioritise corrective action
• 04Use practical tools, checklists and templates that support day-to-day Generative AI & Large Language Models
• 05Leave with a prioritised list of improvements you can start within 30 days

What You Will Take Away

• A practical architecture or workflow blueprint
• A risk and controls checklist for your environment
• Sample datasets, scripts or configurations to reuse

Who Should Attend

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

Prerequisites: No prior specialist knowledge is required.

Training Methodology

Sessions are paced for newcomers — plain-language explanations, worked examples and small-group practice — with time each day for questions. 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