Generative Artificial Intelligence
Learn Generative AI from the basics. Understand how AI generates text, images, audio, and video. Master prompt engineering, LLMs, AI APIs, RAG, and AI agents. Build practical Generative AI applications step by step.
What's Inside Every Lesson?
Every topic is designed so complete beginners can follow along step by step
Interactive Code Editor
Write & run real code in the browser - no setup needed
Practice After Every Topic
Hands-on exercises reinforce what you just learned
Q&A Flip Cards
Common questions answered with simple explanations
Module Quizzes
Test your knowledge before moving to the next module
Mini Projects
Build real apps - a calculator, to-do list, and more
Visual Diagrams
Concepts explained with clear, annotated diagrams
Who This Course Is For
Designed for beginners, students, developers, and working professionals who want to understand how Generative AI works and how to use it in practice. Explains Generative AI concepts using simple language and real-world examples.
Prerequisites
No prior Generative AI knowledge required. Completing the Artificial Intelligence course first is recommended but not required. Basic Python familiarity is helpful for the coding sections.
Published July 2024 · Verified for 2026 Curriculum · Author: Priygop Technical Team
What You'll Learn
- What Generative AI is and how it differs from traditional AI
- How Generative AI generates text, images, audio, and video
- How to write effective prompts that improve AI output
- What LLMs are and how they predict and generate text
- How multimodal AI combines different types of input and output
- How to use AI APIs to build simple Generative AI applications
- What RAG is and how it connects AI to your own data
- What AI agents are and how they automate tasks
- How Generative AI is used across real industries
- AI hallucinations, bias, privacy, copyright, and responsible use
Career Opportunities
Course Modules Overview
Generative AI Fundamentals
12 topics
How Generative AI Works
12 topics
Prompt Engineering
13 topics
Text Generation and Large Language Models
12 topics
AI Image Generation
12 topics
AI Audio and Video Generation
12 topics
Multimodal AI
12 topics
AI APIs and Application Development
13 topics
Retrieval-Augmented Generation
13 topics
AI Agents and Automation
13 topics
Real-World Generative AI Applications
13 topics
Responsible AI and Ethics
13 topics
Complete all 12 modules to unlock your course completion certificate
Course Curriculum
12 comprehensive modules covering everything from basics to advanced topics
Generative AI Fundamentals
Understand what Generative AI is, how it differs from traditional AI and ML, the types of content it creates, and where it is used in the real world.
How Generative AI Works
Discover how Generative AI systems are trained, how they generate output, what tokens and context are, and the difference between training and inference.
Prompt Engineering
Learn how to write effective prompts that produce better AI output. Covers prompt structure, context, instructions, examples, and common mistakes.
Text Generation and Large Language Models
Understand how Large Language Models work, what tokens and context windows are, how chat-based AI is built, and why LLMs sometimes produce wrong answers.
AI Image Generation
Learn how AI creates images from text, how image-to-image works, how to write effective image prompts, and where AI image generation is used in the real world.
AI Audio and Video Generation
Understand how AI generates voice, speech, music, and video. Learn text-to-speech, speech-to-text, text-to-video, and the risks that come with AI-generated media.
Multimodal AI
Learn how multimodal AI combines text, images, audio, and video. Understand vision-language models, image and document understanding, and real-world multimodal applications.
AI APIs and Application Development
Learn how AI APIs work, how to use them safely, and how to build a simple AI application in Python. Covers request/response, API keys, error handling, and security.
Retrieval-Augmented Generation
Understand what RAG is, why it is needed, how embeddings and vector search work simply, and how to connect your own data to an AI model to answer questions.
AI Agents and Automation
Understand what AI agents are, how they differ from AI assistants, how agents use tools and planning to complete goals, and where automation is used in the real world.
Real-World Generative AI Applications
See how Generative AI is transforming education, marketing, healthcare, finance, customer support, cybersecurity, and business automation. Practical problem-to-solution examples.
Responsible AI and Ethics
Learn to use Generative AI responsibly and ethically. Covers AI bias, hallucinations, privacy, transparency, accountability, copyright, environmental impact, safety guidelines, and ethical AI practice.
Your Learning Roadmap
Follow this structured path - from first concepts to production-ready mastery
Understand Generative AI fundamentals, how it works, prompt engineering, and LLMs
Explore AI image, audio, and video generation, multimodal AI, APIs, and RAG
Build AI applications, understand AI agents, real-world applications, safety, and career paths
Understand Generative AI fundamentals, how it works, prompt engineering, and LLMs
Explore AI image, audio, and video generation, multimodal AI, APIs, and RAG
Build AI applications, understand AI agents, real-world applications, safety, and career paths
Practical Projects You Will Build
Apply your Generative Artificial Intelligence skills to create portfolio-ready applications designed to demonstrate real-world proficiency to employers.
Image Classifier
Train a CNN to classify images across 10+ categories using TensorFlow/PyTorch.
- Data preprocessing
- Model training
- Accuracy evaluation
- Web deployment
🎯 A deployed ML model.
NLP Sentiment Analyzer
Build a sentiment analysis system for product reviews using transformer models.
- Text preprocessing
- Fine-tuning
- API endpoint
- Dashboard
🎯 A production NLP pipeline.
Recommendation Engine
Create a product recommendation system using collaborative and content-based filtering.
- Collaborative filtering
- Content-based
- A/B testing
- REST API
🎯 A real-world ML system.
Chatbot with RAG
Build a domain-specific chatbot using Retrieval Augmented Generation with LangChain.
- Document ingestion
- Vector search
- Context-aware answers
- API deployment
🎯 A modern AI application.
Tools & Technologies
Essential tools you'll master during this course
Python
Used for AI API calls and automation scripts
OpenAI API
Access to GPT models for text generation
Jupyter Notebook
Interactive coding environment for AI experiments
Hugging Face
Open-source AI models for text, image, and audio
LangChain
Framework for building AI applications and RAG systems
DALL-E / Stable Diffusion
AI image generation from text prompts
Ready to Start Learning?
Begin your journey with Module 1 and build your skills step by step. Completely free, no registration required.
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