Overview
This 3-day course prepares developers to harness the power of generated AI as they create their solutions. They can craft dynamic content, produce code and documentation, refine user interfaces, and devise customized recommendations. All leading to highly efficient and powerful applications.
Audience
This course will be useful for; software developers, data scientists, ML engineers, AI researchers and more.
Prerequisites
The course is technical in nature and attendees should have the following skills: Python, basic AI concepts, Machine Learning basics, and data storage and access.
Hands-On Environment
The course includes hands-on activities, allowing attendees to reinforce the concepts covered in the course content.
Course Outline
Module 1: Introduction to Generative AI
- Artificial Intelligence
- Introduction to Generative AI
- Generative AI Models
- ChatGPT API
Module 2: Multimodal Generative AI
- Introduction to Multimodal AI
- Text-to-Image Synthesis
- Audio-to-Video Synthesis
- Applications of Multimodal Generative AI
Module 3: Variational Autoencoders
- Introduction to Variational Autoencoders
- Architecture and Training
- Applications of Variational Autoencoders
Module 4: Generative Adversarial Networks
- Introduction to Generative Adversarial Networks
- Architecture and Training
- Common GAN Variants and Applications
Module 5: Natural Language Generation
- Introduction to Natural Language Processing
- Transformer Architecture and Variants
- Applications of NLP in Generative AI
Module 6: Ethics and Responsible AI
- The Importance of AI Ethics
- Bias in Generative Models
- Responsible AI and Best Practices
Module 7: Prompt Engineering
- Creating Effective Prompts
- Evaluating Prompt Performance
- Advanced Prompt Techniques
Module 8: Applications of Generative AI
- Summarizing Documents
- Generating Programming Code
- Virtual Agents
Module 9: Operationalizing Generative AI Models
- Model Selection and Fine-Tuning
- Deployment Strategies
- Monitoring and Maintenance