Generative AI: Foundation Models and Platforms
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Generative AI: Foundation Models and Platforms
This course is part of multiple programs.
Instructor: Rav Ahuja
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What you'll learn
Describe the fundamental concepts of generative AI and its core models
Explain the concept of foundation models in generative AI
Explore the capabilities of pre-trained models for AI-powered applications.
Explore the features, capabilities, and applications of different generative AI platforms, such as IBM watsonx and Hugging Face
Skills you'll gain
Tools you'll learn
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- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 3 modules in this course
This course is for all enthusiasts and practitioners with a genuine interest in the rapidly developing field of generative AI, which is transforming our world.
The course focuses on the core concepts and generative AI models that form the building blocks of generative AI. You will explore deep learning and large language models (LLMs). You will learn about GANs, VAEs, transformers, and diffusion models; the building blocks of generative AI. You will become familiar with the concept of foundation models. You will also learn about the capabilities of pre-trained models and platforms for AI application development and how foundation models use them to generate text, images, and code. You will explore different generative AI platforms like IBM watsonx and Hugging Face. Hands-on labs, included in the course, provide an opportunity to explore the use cases of generative AI through the IBM generative AI classroom and platforms like IBM watsonx. In this course, you will explore different models, such as IBM Granite, OpenAI GPT, Google flan, and Meta Llama. You will also hear from expert practitioners about the capabilities, applications, and tools of generative AI.
In this module, you will dive into the core concepts of generative AI, such as deep learning and LLMs. You will explore the models that form the building blocks of generative AI, including GANs, VAEs, transformers, and diffusion models. You will get acquainted with foundation models and gain insight into how you can use these models as a starting point to generate content.
What's included
6 videos6 readings2 assignments1 app item1 discussion prompt1 plugin
6 videos•Total 31 minutes
- Course Introduction•3 minutes
- Deep Learning and Large Language Models •6 minutes
- Generative AI Models •7 minutes
- Foundation Models•6 minutes
- Expert Viewpoints: Advancing Generative AI Capabilities•4 minutes
- Expert Viewpoints: Exploring Generative AI Capabilities of IBM Watsonx•4 minutes
6 readings•Total 27 minutes
- IBM Product Spotlight: watsonx.governance•2 minutes
- Course Overview•3 minutes
- Specialization Overview •2 minutes
- Helpful Tips for Course Completion•5 minutes
- Lesson Summary•10 minutes
- IBM Granite Foundation Models•5 minutes
2 assignments•Total 22 minutes
- Graded Quiz: Models for Generative AI•12 minutes
- Practice Quiz: Core Concepts and Models of Generative AI•10 minutes
1 app item•Total 15 minutes
- Hands-on Lab: Generative AI Foundation Models•15 minutes
1 discussion prompt•Total 10 minutes
- Working with Foundation Models•10 minutes
1 plugin•Total 5 minutes
- GPT 5 and Google Gemini: Multimodal Foundation Models•5 minutes
In this module, you will learn about pre-trained models and platforms for AI application development. You will explore the ability of foundation models to generate text, images, and code using pre-trained models. You will also learn about the features, capabilities, and applications of different platforms, including IBM watsonx and Hugging Face.
What's included
6 videos2 readings2 assignments2 app items1 plugin
6 videos•Total 33 minutes
- Pre-trained Models: Text-to-Text Generation•7 minutes
- Pre-trained Models: Text-to-Image Generation•5 minutes
- Pre-trained Models: Text-to-Code Generation•7 minutes
- IBM watsonx.ai•6 minutes
- Hugging Face•5 minutes
- Expert Viewpoints: Fostering Innovation through Hugging Face•4 minutes
2 readings•Total 4 minutes
- IBM watsonx.data and watsonx.governance •3 minutes
- Lesson Summary•1 minute
2 assignments•Total 22 minutes
- Graded Quiz: Platforms for Generative AI•12 minutes
- Practice Quiz: Pre-trained Models and Platforms for AI Applications Development•10 minutes
2 app items•Total 65 minutes
- Hands-on Lab: Develop AI Applications with the Foundation Models•45 minutes
- Hands-on Lab: Develop AI Applications for Code Generation•20 minutes
1 plugin•Total 6 minutes
- Key Players in AI•6 minutes
This module includes a graded quiz to test and reinforce your understanding of concepts covered in the course. The module also includes a glossary to enhance comprehension of generative AI-related terms. The module includes a final project, which provides an opportunity to gain hands-on experience on the concepts covered in the course. Finally, the module guides you through the next steps in your learning journey.
What's included
4 readings1 assignment2 app items4 plugins
4 readings•Total 15 minutes
- What's Next: Explore IBM watsonx.governance•1 minute
- Congratulations and Next Steps •10 minutes
- Thanks from the Course Team•2 minutes
- About the Optional Lab: Explore IBM watsonx.ai•2 minutes
1 assignment•Total 21 minutes
- Graded Quiz: Generative AI: Foundation Models and Platforms •21 minutes
2 app items•Total 50 minutes
- Final Project: Working with IBM Granite Foundation Models•45 minutes
- Obtain IBM Cloud Feature Code and Activate Trial Account•5 minutes
4 plugins•Total 90 minutes
- Glossary: Generative AI: Foundation Models and Platforms•15 minutes
- Creating an IBM Cloud Account•15 minutes
- Hands-on Lab: Explore IBM watsonx.ai•30 minutes
- Hands-on Lab: Explore Hugging Face•30 minutes
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Showing 3 of 339
Reviewed on Apr 18, 2026
Easily understandable and coding with watsonx is a great way for learning and hand on experience with simple way.
Reviewed on Feb 16, 2025
This course all the basics for AI and it is interesting too
Reviewed on Mar 22, 2024
Some course materials are biased toward the IBM platform
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