Practical Workshop in Machine Learning Fundamentals

Course Introduction

Over five focused days, this workshop-based course takes Machine Learning Fundamentals out of the textbook and into the reality of data, analytics and automation initiatives. Participants work through regional case material, structured exercises and peer discussion, leaving with methods they can apply on their next working day.

Training Objectives

• 01Build a shared vocabulary and framework for Machine Learning Fundamentals that your whole team can use
• 02Apply proven methods for Machine Learning Fundamentals to realistic scenarios drawn from data, analytics and automation initiatives
• 03Anticipate the failure points and compliance issues that most often affect Machine Learning Fundamentals
• 04Communicate Machine Learning Fundamentals decisions clearly to colleagues, clients and management
• 05Prepare a personal action plan to apply Machine Learning Fundamentals 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: Open to all levels; participants are encouraged to bring a real work challenge.

Training Methodology

Learning happens by doing — teams work through practical tasks, present their results and receive immediate feedback. Case material and examples are drawn from data, analytics and automation initiatives.

Day-by-Day Programme (5 Days)

• Day 1
  Where Machine Learning Fundamentals fits

  How Machine Learning Fundamentals connects to wider operations in data, analytics and automation initiatives, plus the essential vocabulary.

• Day 2
  Working with the standards

  Interpreting and applying the codes and good-practice guidance that govern Machine Learning Fundamentals.

• Day 3
  Tools and techniques lab

  Guided practice with the tools, checklists and templates used for Machine Learning Fundamentals.

• Day 4
  Risk, compliance and case review

  Analysis of incidents and cases to see where Machine Learning Fundamentals succeeds or breaks down.

• Day 5
  Consolidate and plan

  Capstone discussion, action planning and a closing assessment.

Upcoming Sessions