Unit 2 · Intro to AI

Generative AI

4 min read Updated May 19, 2026

Unit Introduction

Welcome to the second unit of the AI Fundamentals course!

In this unit, you will learn about generative AI (GenAI), one of the most used AI technologies today.

You will learn: what is generative AI

how it works

where it can be used Let’s start!

What is generative AI?

Generative AI or GenAI is a category of artificial intelligence that creates new content, such as text, images, audio, and video.

GenAI uses deep learning algorithms to recognize patterns from large datasets and generates content based on user prompts or requests. It’s the technology behind tools like ChatGPT or Gemini.

How is text generated?

Let’s focus on text generation. It begins with unsupervised and supervised learning, where models, such as Large Language Models (LLMs), are trained on vast datasets that include

examples of text, images, audio, video or code.

During training, LLMs break down text into smaller parts, called tokens, and then predict the most likely words to follow based on the context.

They do this using a technology called transformers, which helps them understand the relationships between different parts of the data, like how words fit together in sentences. The models that use the transformer are called GPT (Generative Pre-trained Transformer) models.

🔑 Key Concept A transformer is a type of neural network used in machine learning, especially for understanding language. It’s designed to process data like sentences by focusing on different parts of the input using an attention mechanism. It is a technique that allows transformers to look at all words in a sentence at once instead of one by one, helping them understand context more effectively. This design is the foundation for many advanced AI models, like Large

Language Models (LLMs), which use transformers to understand and generate human-like text.

Once trained, these models can generate new content by predicting what should come next based on the patterns they’ve learned.

In the next course you will learn about this in more detail.

2 2 2 GenAI application

GenAI can be used in various contexts, with thousands of tools available for

each application. Here you will explore some examples that highlight GenAI’s

broad potential.

Content creation

Personalization

Extraction and analysis

Transcription and translation

Matching

Code generation Contentcreation

Content creation

Text Image Generation Generation

Writing articles, blog posts, Creating original artwork or and marketing content. product images.

Music Video Composition Generation

Composing new songs or Generating animations of soundtracks. promotional videos. Personalization

Personalization

Personal Chatbots Assistants

Providing personalized Enhancing customer service responses and with conversational agents. recommendations. Recommendation Tailored systems marketing

Suggesting products, music, or Creating personalized content based on user marketing messages for users. preferences.

Extraction and analysis

Extraction and analysis

Text Data Extraction Summarization

Condensing long articles or Pulling specific information reports into key points. from large datasets.

Data Analysis

Extracting insights from large

datasets and presenting them.

Transcriptionandtranslation

Transcription and translation Speech Language Recognition Translation

Converting spoken language Translating text from one into text. language to another.

Matching

Matching

Applicant-job Company-segment Matching Matching

Identifying candidates whose Identifying the best market skills align with job segments for a company’s

requirements. products or services.

Code generation

Code generation

Code Automated Completion Testing

Assisting developers by Generating test cases for

suggesting code snippets. software applications.

AI agents

AI agents use GenAI to go beyond just generating content, they can act, make decisions, and carry out tasks autonomously. An AI agent is a system that works on its own to observe its surroundings, make decisions, and take actions to reach a goal. AI agents are designed to perform tasks or make decisions without direct and continuous input from the user.

AI agents leverage GenAI to generate responses, analyze data, and make decisions, allowing them to perform tasks independently. AI agents have various applications, such as virtual assistants, customer service chatbots, and autonomous vehicles.

Think of a janitor who works independently to keep the school clean and organized. You will learn more about AI agents in the AI agents course in this learning path.

Continuetothewrapupforthisunit

Wrap up

Generative AI (GenAI) is a type of AI that creates new content such as text, images, audio, and video. It’s used for content creation, personalization, extracting and analyzing information, transcription and translation, matching data, and even generating code.

GenAI learns patterns from large datasets using deep learning and transformers. It breaks data into smaller parts, understands the relationships between them, and then predicts what comes next to generate content based on user prompts.

AI agents use GenAI to analyze information, make decisions, and carry out tasks independently.

Unit complete!

Well done!

You have completed the AI Fundamentals course! In the next course you will dive deep into how GenAI works by

focusing on LLMs.

Mark this task complete to continue to the next unit.