Machine Learning & Applied AI Bootcamp

About Course

5-Day Intensive Live Online Training Programme

Upcoming dates: Available on request.

Machine Learning & Applied AI Bootcamp is an intensive, instructor-led training programme designed for professionals who want practical experience in how machine learning and applied AI are used to solve real business and operational problems. The course combines guided teaching, live demonstrations, hands-on exercises, and applied project work so participants build real understanding through practice rather than observation alone.

Across five immersive days, participants work through the core stages of the machine learning workflow, from understanding data and selecting suitable approaches to building, testing, and interpreting models in practical scenarios. The focus is on applied learning, helping professionals understand not only what machine learning is, but how it can be used responsibly and effectively in realistic organisational contexts.

Participants who successfully complete the training will receive a Certificate of Completion from London Global Centre. Training is delivered by experienced trainers with strong professional and industry backgrounds.

 

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What Will You Learn?

  • Understand the core concepts, terminology, and workflows used in machine learning and applied AI.
  • Explore how data is prepared, analysed, and used to support model development and decision-making.
  • Apply machine learning techniques to practical tasks such as prediction, classification, and pattern recognition.
  • Interpret model outputs, evaluate performance, and recognise common limitations and risks.
  • Gain hands-on experience through guided labs, exercises, and applied case-based activities.
  • Understand how machine learning and AI can be used across different industries and business functions.

Course Content

Day 1: Foundations of Machine Learning and Applied AI

  • Introduction to machine learning, applied AI, and how intelligent systems are used in real-world organisations.
  • Core concepts including supervised and unsupervised learning, features, labels, datasets, and model workflows.
  • Exploring practical machine learning use cases across business, operations, customer service, and analytics.
  • Guided exercises to identify suitable AI and machine learning applications in realistic scenarios.

Day 2: Data Preparation and Exploration

Day 3: Building Machine Learning Models

Day 4: Interpreting Results and Improving Performance

Day 5: Applied AI Project and Real-World Relevance