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Foundation Models and Generative AI Platforms

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BeginnerCourse

Understanding the core concepts and foundational models of generative AI gives you the footing that you need in the rapidly developing field of generative AI, which is transforming our world. Along with deep learning and LLMs, you'll explore GANs, VAEs, transformers, and diffusion models, which are the building blocks of generative AI. This course is for all enthusiasts and practitioners with an interest in learning what generative AI is and how it works.

Language

  • English

Topic

  • Artificial Intelligence

Industries

  • Information Technology

Enrollment Count

  • 73

Skills You Will Learn

  • Artificial Intelligence, LLM, Generative AI, NLP, Foundation Models

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 6 hours

Platform

  • SkillsNetwork

Last Update

  • March 25, 2025
About this Course
Focusing on the core concepts and foundational AI models that form the building blocks of generative AI, this course provides a base to help you build your generative AI skills. Explore deep learning and large language models (LLM) while learning about GANs, VAEs, transformers, and diffusion models, which are the building blocks of generative AI. 

In the course, you'll become familiar with the concept of foundation models, learn about the capabilities of pretrained models and platforms for AI application development, and explore how foundation models use them to generate text, images, and code. You will also explore different generative AI platforms like IBM watsonx and Hugging Face. The included hands-on labs provide an opportunity to explore the use cases of generative AI. In this course, you will explore different models, such as IBM Granite, OpenAI GPT, Google flan, and Meta Llama , and hear from expert practitioners about the capabilities, applications, and tools of generative AI.

This course is designed for everyone an interest in the rapidly developing field of generative AI, which is transforming our world. 

Course Syllabus

Models for Generative AI
  • Course Introduction
  • Deep Learning and Large Language Models
  • Generative AI Models
  • Foundation Models
Platforms for Generative AI
  • Pre-trained Models: Text-to-Text Generation
  • Pretrained Models: Text-to-Image Generation
  • Pretrained Models: Text-to-Code Generation
  • IBM watsonx.ai: generative AI for Business
  • Hugging Face: Open Source  Generative AI
Course Quiz, Project, and Wrap-up

Recommended Skills Prior to Taking this Course

This course is for anyone wanting to learn and get familiar with the concepts of generative AI. No prior knowledge is required for this course. Note that this platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.

Instructors

Leon Katsnelson

Director & CTO, IBM Developer Skills Network

I've had a very productive career in tech. I've touched many areas from mainframe, to manufacturing automation (IoT), to databases, big data, data science and AI, blockchain, and of course full stack and cloud-native development and DevOps. I started my career in test and QA, did quite a bit of development, product management, team leadership, and people management before becoming an executive. I had some great wins including bringing to market a billion $ product. And had some failures along the way. But throughout my career, one thing has always remained constant. I learned everything I could and used every chance I had to get a new skill. My goal in life is to help those who have an appetite for learning to acquire knowledge and skill to build their career or simply become better users of the latest tech.

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Rav Ahuja

Global Program Director, IBM Skills Network

Rav Ahuja is a Global Program Director at IBM. He leads growth strategy, curriculum creation, and partner programs for the IBM Skills Network. Rav co-founded Cognitive Class, an IBM led initiative to democratize skills for in demand technologies. He is based out of the IBM Canada Lab in Toronto and specializes in instructional solutions for AI, Data, Software Engineering and Cloud. Rav presents at events worldwide and has authored numerous papers, articles, books and courses on subjects in managing and analyzing data. Rav holds B. Eng. from McGill University and MBA from University of Western Ontario.

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