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Generative AI

Learn how modern AI creates text, images, audio, video, and code.

Level: Beginner to AdvancedDuration: 8 WeeksMode: OnlineLanguage: EnglishCertificate: Available after successful completion
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Course overview

Generative AI is the technology behind tools like ChatGPT, Midjourney, and AI video generators — models that don't just analyse data, they create new text, images, sound, and code from a prompt.

This course takes you from the fundamentals of artificial intelligence through to building your own AI-powered applications. You'll learn the theory behind large language models and diffusion models, then get hands-on with prompt engineering, content generation, and real projects you can put in a portfolio.

By the end, you'll understand how these systems actually work, how to use them responsibly, and how to build something with them — not just how to type prompts into a chat box.

Learning objectives

By the end of this course, you'll be able to:

  • Explain how machine learning, deep learning, and generative AI relate to each other
  • Describe how large language models are trained and how they generate text
  • Write effective, structured prompts for text, image, audio, and video generation
  • Use generative AI tools to produce written content, images, and multimedia
  • Build a simple AI chatbot or AI-powered application
  • Identify ethical risks, privacy issues, and the current limitations of generative AI
  • Complete a capstone project applying multiple generative AI techniques together

Complete syllabus

0 / 10 modules complete

Tick off each module as you finish it — your progress is saved on this device.

  1. 1. Introduction to Artificial Intelligence

    What AI is, a short history, and where generative AI fits among other kinds of AI systems.

  2. 2. Machine Learning and Deep Learning Basics

    Supervised vs. unsupervised learning, neural networks, and why depth and data made modern AI possible.

  3. 3. Introduction to Generative AI

    How generative models differ from predictive ones, and a tour of the major model families (GANs, diffusion, transformers).

  4. 4. Large Language Models (LLMs)

    Tokenization, attention, and next-token prediction — how models like GPT and Llama actually generate text.

  5. 5. Prompt Engineering Techniques

    Zero-shot vs. few-shot prompting, chain-of-thought, system prompts, and iterating on prompts systematically.

  6. 6. AI Text and Content Generation

    Using LLMs for writing, summarising, translating, and editing — and where they tend to go wrong.

  7. 7. AI Image, Audio, and Video Generation

    Diffusion models, text-to-image and text-to-video tools, and voice/audio generation basics.

  8. 8. Building AI Chatbots and Applications

    Connecting a model to a simple interface: system prompts, context, memory, and API basics.

  9. 9. Responsible AI, Ethics, Privacy, and Limitations

    Bias, hallucination, copyright, data privacy, and how to use generative AI tools responsibly.

  10. 10. Practical Projects and Final Assessment

    Apply everything in a capstone project, then take the final quiz to unlock your certificate.

Required skills & prerequisites

  • No coding experience required — module 8 introduces basic building blocks gently
  • Comfortable using a web browser and everyday apps
  • Curiosity about how AI tools work under the hood
  • High-school level maths is helpful but not required

Tools & technologies

ChatGPT / other LLM chat interfacesOpenAI-compatible or Groq APIs (for the chatbot module)An image generation tool (e.g. Stable Diffusion or similar)A text editor or notebook for light, optional scripting

Practical projects

01

AI writing assistant

Design a prompt system that turns rough notes into a polished blog post in a consistent voice.

02

Prompt-engineered image set

Produce a themed set of AI-generated images using iterative, structured prompting.

03

Mini AI chatbot

Build a simple chatbot with a defined persona, system prompt, and guardrails for a specific use case.

04

Capstone: end-to-end AI mini-app

Combine text and image generation into one small project you can show in a portfolio.

Instructor

AI

The AI Tutor Team

Course design & AI tutoring

This course was built by the same team behind AI Tutor's step-by-step tutoring approach. Every module is paired with an AI tutor you can question directly — ask it to re-explain any concept at your own level, in your own words.

Frequently asked questions

No. The course is designed for complete beginners. Module 8 introduces just enough building blocks to connect a chatbot to a simple interface, explained step by step.

It's designed as an 8-week course at a few hours a week, but it's entirely self-paced — go faster or slower as you like.

Work through the modules, then pass the short final quiz on this page (70% or higher). Your certificate becomes available to download immediately.

Yes — every module links to the AI Tutor chat, pre-set to the Generative AI subject, so you can ask follow-up questions any time.

This page is the structured course: syllabus, projects, quiz, and certificate. "Start Learning" opens the same AI tutor you'd use for any subject, already set to Generative AI.

Final quiz & certificate

Score 70% or higher to unlock your certificate. You can retake the quiz as many times as you like.

1. What best describes generative AI?

2. In a large language model, text is broken into small chunks before processing. What are these chunks called?

3. Which technique involves giving a model a few worked examples inside the prompt itself?

4. Diffusion models, commonly used for image generation, work primarily by:

5. Which of these is a real limitation of today's generative AI models?

6. "Responsible AI" in this course's context most closely means:

Ready to start Generative AI?

Free to start. Enroll, then jump straight into module one.