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AI and ML Fundamentals

From perceptrons to transformers: a practical introduction to artificial intelligence and machine learning for engineers.

Beginner1.1 hours10 lessons
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What You'll Learn

  • โœ“Distinguish between AI, machine learning, deep learning, and generative AI
  • โœ“Understand the three main types of machine learning: supervised, unsupervised, and reinforcement
  • โœ“Walk through the end-to-end ML lifecycle from problem framing to deployment and monitoring
  • โœ“Recognise common algorithms: linear regression, decision trees, k-means, and gradient boosting
  • โœ“Explain how neural networks learn through forward and backward propagation
  • โœ“Understand the transformer architecture that powers modern large language models
  • โœ“Apply prompt engineering techniques: zero-shot, few-shot, chain-of-thought, and RAG
  • โœ“Identify ethical risks in AI: bias, hallucination, privacy, and copyright
  • โœ“Map AI/ML services across AWS (SageMaker, Bedrock), Azure (AI Foundry), and Google Cloud (Vertex AI)
  • โœ“Choose the right tool for an AI use case: build, fine-tune, or call a managed API

Prerequisites

  • โ€ขBasic programming familiarity (Python is a plus but not required for this course)
  • โ€ขHigh school level mathematics โ€” no calculus or linear algebra required

Course Curriculum

Practice for the Real Exam

After completing this course, test yourself with exam-style practice questions.