Module 3 Overview: AI Core Concepts

  • AI
  • AI Literacy

What's really happening inside AI — and how does it shape the technology you use every day.

In this module, you’ll build foundational knowledge of how core AI systems work. You’ll explore relationships between AI, Machine Learning, Deep Learning, and Generative AI, including their structures, processes, and real-world applications. By understanding these fundamentals, you’ll be prepared to critically evaluate and use AI technologies across a range of contexts.

By the end of this module, you will be able to:

  • Describe the differences and relationships among AI, Machine Learning, Deep Learning and Generative AI.
  • Define supervised, unsupervised and reinforcement machine learning algorithms and explain their fundamental processes.
  • Describe the basic structure and components of a Deep Learning Neural Network (input layer, hidden layers, output layer).
  • Define Generative AI and identify at least two current real-world applications of Generative AI.

Content Preview

Below you'll find the topics you'll cover in this module, helping you build a clear understanding of the key ideas. After that, you'll see the activities you'll complete, giving you hands-on practice to apply what you've learned

Topics

In this module, you'll explore these topics:

  • The Landscape of AI: Machine Learning, Deep Learning, and Generative AI: Many AI systems require data and an algorithm to produce an outcome.

  • Introduction to Machine Learning: Using self-learning algorithms, like supervised, unsupervised, reinforcement, and deep learning, computers learn from data in order to recognize patterns or predict outcomes.

  • Introduction to Neural Networks: Using "brain-like" algorithms, neural networks learn from data to recognize patterns or predict outcomes.

  • Introduction to Generative AI: Using Foundational Models and Large Language Models, computers learn from data and then create new artifacts like video, images, text, etc.

Activities

You'll apply your learning through these activities:

  • CREATE: Produce a visual diagram (like a Venn diagram or concept map) clearly illustrating and explaining the relationships among AI, Machine Learning, Deep Learning, and Generative AI.
  • QUIZ: Match definitions with AI-related terms.
  • BUILD: Build a simple supervised ML model using Teachable Machine.