Advanced Techniques in Generative AI
Workshop Duration: 2 Days
Overview : This 2-day workshop provides a comprehensive exploration of advanced generative AI topics, from deep learning architectures to practical applications and ethical considerations
Target Audience: Developers, Data Scientists, and AI Practitioners with a foundational understanding of AI/ML and neural networks
Takeaways:
- Workshop slides and reference materials
- Access to further resources, including advanced research and tools
- Certificate of Completion
Mode: Online/Offline
Course Outline
Day 1: Advanced Generative Models and Techniques
1. Deep Dive into Transformer Models
- Duration: 1.5 hours
- Content:
- Overview of Transformer Architecture: Attention Mechanisms and Multi-Head Attention
- Understanding BERT, GPT, and Their Variants (e.g., GPT-4, BERT-based models)
- Fine-tuning Pre-trained Transformers for Specific Tasks
- Hands-on: Fine-tune a GPT-3/4 model for a specific text generation task
2. Advanced Generative Models
- Duration: 2 hours
- Content:
- Introduction to Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs)
- Exploring Conditional GANs, CycleGANs, and StyleGANs
- Applications: Image Synthesis, Data Augmentation, and Artistic Creation
- Hands-on: Implement a GAN or VAE to generate synthetic images
3. Large-Scale Generative AI Systems
- Duration: 1.5 hours
- Content:
- Scaling Generative Models: Distributed Training and Fine-Tuning
- Handling Large Datasets and Computational Resources
- Techniques for Efficient Model Deployment and Inference
- Hands-on: Use cloud resources to train a large-scale generative model
4. Text Generation and Fine-Tuning
- Duration: 1 hours
- Content:
- Advanced Techniques in Text Generation: Prompt Engineering and Control
- Leveraging Pre-trained Models for Custom Text Generation
- Managing Token Limitations and Handling Long Contexts
- Hands-on: Develop a custom text generation model with advanced prompting techniques
Day 2: Applications, Ethics, and Future Trends in Generative AI
1. Practical Applications of Generative AI
- Duration: 2 hours
- Content:
- Use Cases in Various Industries: Healthcare, Finance, Entertainment
- Building AI-Powered Tools: Chatbots, Content Creation, and Automated Design
- Case Studies of Successful Generative AI Implementations
- Hands-on: Develop a simple application using generative AI, such as a content generation tool
2. Ethical Considerations and Responsible AI
- Duration: 1.5 hours
- Content:
- Ethical Implications of Generative AI: Misinformation, Deepfakes, and Bias
- Strategies for Ensuring Fairness and Transparency
- Regulatory and Compliance Considerations
- Hands-on: Analyze a case study involving ethical dilemmas in generative AI
3. Evaluating and Tuning Generative Models
- Duration: 1.5 hours
- Content:
- Metrics for Evaluating Generative Models: Inception Score, FID Score, BLEU Score
- Techniques for Hyperparameter Tuning and Model Optimization
- Understanding Model Interpretability and Debugging
- Hands-on: Evaluate and fine-tune a generative model using appropriate metrics
4. Future Trends and Research Directions in Generative AI
- Duration: 1 hours
- Content:
- Emerging Trends: Zero-Shot Learning, Multi-Modal Models, and Federated Learning
- Current Research Papers and Innovations in Generative AI
- Preparing for the Next Generation of AI Technologies
- Hands-on: Explore and discuss recent research papers or innovations in generative AI
5. Final Project: Building and Deploying a Generative AI Solution
- Duration: 1.5 hours
- Content:
- Requirements: Develop and deploy a complete generative AI solution (e.g., a chatbot, image generator, or text summarizer)
- Use a pre-trained model or build from scratch
- Implement and integrate the solution into a real-world scenario
- Hands-on: Participants work on building, testing, and deploying their generative AI project
- Requirements: Develop and deploy a complete generative AI solution (e.g., a chatbot, image generator, or text summarizer)