(Beginner-Friendly Learning Path)
Module 1: Introduction to Generative AI
| # | Topic | Link |
|---|
| 1 | What is Generative AI? | Start → |
| 2 | How Generative AI Differs from Traditional AI | Start → |
| 3 | Types of Generative AI Models: GANs, VAEs, Transformers | Start → |
| 4 | Real-World Applications of Generative AI: A Case Study of “Imaginarium Inc.” | Start → |
| 5 | Ethical Considerations and Responsible Use of Generative AI | Start → |
Module 2: Understanding Generative Adversarial Networks (GANs)
| # | Topic | Link |
|---|
| 1 | The Architecture of GANs: Generator and Discriminator | Start → |
| 2 | How GANs Learn: The Adversarial Process | Start → |
| 3 | Common GAN Architectures: DCGAN, StyleGAN | Start → |
| 4 | Network Topologies and Architectures | Start → |
| 5 | Training a Simple GAN for Image Generation (Hands-on) | Start → |
| 6 | Evaluating GAN Performance: Metrics and Visual Inspection | Start → |
Module 3: Variational Autoencoders (VAEs)
| # | Topic | Link |
|---|
| 1 | Introduction to Autoencoders: Encoding and Decoding | Start → |
| 2 | The Variational Approach: Latent Space and Probability Distributions | Start → |
| 3 | VAE Architecture and Loss Function | Start → |
| 4 | Building a VAE for Anomaly Detection (Hands-on) | Start → |
| 5 | Comparing GANs and VAEs: Strengths and Weaknesses | Start → |
Module 4: Transformer Models and Language Generation
| # | Topic | Link |
|---|
| 1 | Introduction to Transformer Architecture: Attention Mechanism | Start → |
| 2 | Understanding Language Models: GPT, BERT, and Beyond | Start → |
| 3 | Text Generation with Transformers: A Practical Overview | Start → |
| 4 | Fine-tuning a Pre-trained Transformer for Text Summarization (Hands-on) | Start → |
| 5 | Prompt Engineering: Crafting Effective Prompts for Generative AI | Start → |
Module 5: Image Generation with DALL-E and Stable Diffusion
| # | Topic | Link |
|---|
| 1 | Introduction to DALL-E and Image Generation from Text | Start → |
| 2 | Understanding Stable Diffusion: Latent Diffusion Models | Start → |
| 3 | Using Pre-trained Models for Image Synthesis (Hands-on) | Start → |
| 4 | Exploring Image Editing and Manipulation with Generative AI | Start → |
| 5 | The Future of Image Generation: Trends and Possibilities | Start → |
Module 6: Generative AI for Audio and Music
| # | Topic | Link |
|---|
| 1 | Introduction to Generative AI for Audio | Start → |
| 2 | Generating Music with AI: Techniques and Tools | Start → |
| 3 | Speech Synthesis and Voice Cloning | Start → |
| 4 | Creating Sound Effects and Audio Textures (Hands-on) | Start → |
| 5 | The Potential of AI in Music Production and Sound Design | Start → |
Module 7: Practical Applications and Future Trends
| # | Topic | Link |
|---|
| 1 | Generative AI in Art and Design: Creating Unique Content | Start → |
| 2 | Generative AI in Marketing: Personalized Content Generation | Start → |
| 3 | Generative AI in Healthcare: Drug Discovery and Diagnosis
Limit reached
| Start → |
| 4 | The Future of Generative AI: Emerging Trends and Challenges | Start → |
| 5 | Building Your Own Generative AI Project: A Step-by-Step Guide | Start → |
