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Beginner's Guide to Generative AI
These tutorials will provide you with a solid foundation in Generative AI and prepare you for your career goals.
Introduction to Generative AI
- Introduction to Generative AI
- History and Evolution of Generative AI
- Applications of Generative AI
- Generative AI vs Traditional AI
- Popular Generative AI Models
- Ethical Considerations in Generative AI
- Generative AI in Various Industries
Fundamentals of Generative Models
- Generative Adversarial Networks (GANs)
- What are GANs?
- Architecture of GANs: Generator and Discriminator
- Variants of GANs: DCGAN, CycleGAN, StyleGAN
- Variational Autoencoders (VAEs)
- Understanding VAEs
- Applications of VAEs
- Transformers
- Overview of Transformer Models
- Introduction to GPT and BERT
- Applications in Text Generation
Core Technologies in Generative AI
- Deep Learning Basics for Generative AI
- Neural Networks Overview
- Introduction to Natural Language Processing (NLP)
- Computer Vision for Image and Video Generation
- Reinforcement Learning and Its Role
Data Preparation and Processing
- Dataset Collection for Generative Models
- Data Cleaning and Preprocessing
- Labeling and Annotation Techniques
- Working with Large Datasets
Training and Optimizing Generative Models
- Loss Functions in Generative AI
- Model Training Basics
- Overfitting and Underfitting in Generative Models
- Hyperparameter Tuning
- Using Pre-trained Models
- Transfer Learning for Generative AI
Programming and Implementation
- Setting Up the Development Environment
- Introduction to PyTorch for Generative AI
- TensorFlow Basics for Generative AI
- Building a Simple GAN
- Implementing a VAE
- Fine-Tuning a Transformer Model
- Evaluation Metrics for Generative Models
Applications of Generative AI
- Text Generation
- Writing Articles and Stories
- Chatbot Development
- Image and Video Generation
- Style Transfer
- Creating Deepfakes
- Audio and Music
- Generation Composing Music
- Speech Synthesis
- Synthetic Data Generation
- Drug Discovery and Medical Applications
Advanced Topics in Generative AI
- Multimodal Generative AI
- Large Language Models (LLMs)
- GPT Series Overview
- Using OpenAI Models
- Explainability in Generative AI
- Handling Bias in Generative AI Systems
- Generative AI for Personalization
Libraries and Tools
- Hugging Face for NLP
- OpenCV for Computer Vision
- Generative AI APIs: OpenAI, Google AI
- Frameworks: PyTorch Lightning, Keras
- Model Deployment with TensorFlow Serving
- Cloud Platforms for Generative AI
Hands-On Projects
- Building a Text Generator
- Developing a Style Transfer Application
- Creating a Deepfake Video
- Synthesizing Music Using Generative Models
- Designing a Personalized Chatbot
- Generating Synthetic Data for Training
Math and Algorithms in Generative AI
- Understanding Latent Spaces
- Random Sampling Techniques
- Gradient Descent in Model Optimization
- Matrix Operations in AI Models
- Probability in Generative Processes
Ethical and Societal Considerations
- Addressing Bias in Generative AI
- Combating Misinformation
- Regulatory Frameworks for Generative AI
- Privacy Concerns and Data Security
Evaluation and Deployment
- Evaluating Model Performance
- Metrics: BLEU, FID, and Perplexity
- Optimizing Models for Scalability
- Deploying Generative AI Models
Capstone Projects
- Real-time AI Image Generation App
- Multi-language Chatbot for Customer Support
- AI-Powered Creative Writing Tool
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