Learn how to get started using cloud-based generative AI services and tools like Amazon SageMaker, Google Cloud AI Platform, OpenAI, ChatGPT, and more.
Overview
Syllabus
Introduction
- Cloud-based generative AI
- Introduction to cloud-based generative AI
- The business value of generative AI on cloud platforms
- Introduction to cloud-based storage and data management
- Introduction to cloud-based tools for model training and deployment
- Introduction to cloud-based APIs for generative AI
- Introduction to cloud-based generative models for image and video data
- Introduction to Generative Adversarial Networks (GANs) on the cloud
- Challenge: Set up cloud services for generative AI
- Solution: Set up cloud services for generative AI
- Introduction to cloud-based generative AI models for text data
- Overview of natural language processing (NLP) techniques for text generation
- Cloud-based tools for training language models
- Music modeling with recurrent neural networks (RNNs) on the cloud
- The future of generative AI in the cloud
- Art and music generation use case
- Game development use case
- Text generation use case
- Image and video generation use case
- Data augmentation use case
- Personalization use case
- Medical diagnosis use case
- Robotics use case
- Other emerging use cases
- Challenge: Get creative with art
- Solution: Get creative with art
- Explore Amazon SageMaker
- Google Cloud AI Platform
- AI and Microsoft Azure
- AI on IBM Watson
- Understanding OpenAI
- Demo: OpenAI API
- Edge computing and cloud-based generative AI
- Federated learning for distributed generative models on the cloud
- Security and privacy issues in cloud-based generative AI
- Overview of generative AI ethics in the cloud
- Challenge: Generative AI on the edge of clouds
- Solution: Generative AI on the edge of clouds
- Trying out cloud-based generative AI
Taught by
David Linthicum