This course focuses on the core concepts and models of generative AI, including deep learning and large language models. It covers the concept of foundation models and the capabilities of pre-trained models and platforms for AI application development.
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This course is designed for enthusiasts and practitioners who share an interest in the rapidly advancing field of generative AI.
This course centers around the core concepts and generative AI models that form the building blocks of generative AI. You will delve into the concepts of deep learning and large language models (LLMs). You will learn about GANs, VAEs, transformers, and diffusion models – the fundamental components of generative AI.
You will learn about the concept of foundation models. You will gain insights into the capabilities of pre-trained models and platforms for AI application development. The course will also cover how foundation models utilize these platforms to generate text, images, and code. Additionally, participants will explore various generative AI platforms such as IBM watsonX and Hugging Face.
The course includes practical hands-on labs, offering participants the chance to delve into the applications of generative AI using the IBM Generative AI Classroom and platforms like IBM watsonX. Throughout the course, you'll have the opportunity to explore various models, including IBM Granite, OpenAI GPT, Google Flan, and Meta Llama. Additionally, expert practitioners will share insights into the capabilities, applications, and tools of generative AI.
This course is part of the Generative AI for Everyone Professional Certificate.
What you'll learn
- Describe the fundamental concepts of generative AI.
- Explore the building blocks of generative AI, including GANs, VAEs, transformers, and diffusion models.
- Explain the concept of foundation models in generative AI.
- Explore the ability of foundation models to generate text, images, and code using pre-trained models.
- Describe the features, capabilities, and applications of different generative AI platforms, including IBM watsonx and Hugging Face.
Syllabus
Module 1: Models for Generative AI
Video: Course Introduction
Reading: Course Overview
Reading: Program Overview
Reading: Helpful Tips for Course Completion
Video: Deep Learning and Large Language Models
Video: Generative AI Models
Video: Foundation Models
Hands-on Labs: Generative AI Foundation Models
Reading: Module Summary
Practice Quiz: Core Concepts and Models of Generative AI
Discussion Prompt: Working with Foundation Models
Reading: IBM Granite Foundation Models
Graded Quiz: Models for Generative AI
Module 2: Platforms for Generative AI
Video: Pre-trained Models: Text-to-Text Generation
Hands-on Lab: Develop AI Applications with the Foundation Models
Video: Pre-trained Models: Text-to-Image Generation
Video: Pre-trained Models: Text-to-Code Generation
Hands-on Lab: Develop AI Applications for Code Generation
Video: IBM watsonx.ai
Video 5: Hugging Face
Reading: Module Summary
Practice Quiz: Pre-trained Models and Platforms for AI Applications Development
Graded Quiz: Platforms for Generative AI
Module 3: Course Quiz, Project, and Wrap-up
Glossary - Generative AI: Foundation Models and Platforms
Final Project: Working with IBM Granite Foundation Models
Graded Quiz: Generative AI: Foundation Models and Platforms
Reading: Congratulations and Next Steps
Reading: Thanks from the Course Team
