Models and Platforms for Generative AI
Learn core generative AI concepts, models, and platforms including deep learning, LLMs, foundation models, and how to build AI applications.
Learn core generative AI concepts, models, and platforms including deep learning, LLMs, foundation models, and how to build AI applications.
This introductory course is designed for enthusiasts and practitioners interested in the rapidly evolving field of generative AI. The curriculum focuses on the fundamental concepts and models that form the building blocks of generative AI systems. Students will explore deep learning principles and large language models (LLMs), gaining comprehensive knowledge of key architectures including GANs, VAEs, transformers, and diffusion models. The course introduces the concept of foundation models and provides insights into how pre-trained models and platforms can be leveraged for AI application development. Participants will learn how these foundation models generate text, images, and code, while exploring various generative AI platforms such as IBM watsonX and Hugging Face. The learning experience includes practical hands-on labs in the IBM Generative AI Classroom, allowing students to experiment with models including IBM Granite, OpenAI GPT, Google Flan, and Meta Llama. Throughout the course, expert practitioners share insights about capabilities, applications, and tools in the generative AI landscape, providing a well-rounded understanding of this transformative technology.
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What you'll learn
Describe the fundamental concepts and building blocks of generative AI Understand deep learning principles and large language models (LLMs) Explore key architectures including GANs, VAEs, transformers, and diffusion models Explain the concept and applications of foundation models in generative AI Learn how foundation models generate text, images, and code using pre-trained models Develop practical skills with hands-on labs using IBM watsonX and Hugging Face Compare features and capabilities of different generative AI platforms Build AI applications using foundation models for various generative tasks
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, Exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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There are 3 modules in this course
This comprehensive course introduces the fundamental concepts and practical applications of generative AI. Students learn about the core building blocks of generative AI technologies, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), transformer architectures, and diffusion models. The curriculum explores how these technologies enable the creation of foundation models capable of generating text, images, and code. Special emphasis is placed on understanding large language models (LLMs) and their applications across various domains. The course provides hands-on experience with leading generative AI platforms, including IBM watsonX and Hugging Face, allowing students to work with models such as IBM Granite, OpenAI GPT, Google Flan, and Meta Llama. Through practical labs and expert insights, participants gain a solid understanding of how to develop AI applications using pre-trained models, preparing them for further exploration and implementation of generative AI technologies in real-world contexts.
Models for Generative AI
Module 1
Platforms for Generative AI
Module 2
Course Quiz and Final Project
Module 3
Fee Structure
Payment options
Financial Aid
Instructor
Technology Education and Skills Development Leader at IBM
Rav Ahuja serves as the Chief Content Officer and Global Program Director at IBM Skills Network, where he leads curriculum creation, growth strategy, and partner programs. After earning his B.Eng. from McGill University and MBA from the University of Western Ontario, he co-founded Cognitive Class, an IBM initiative focused on democratizing access to in-demand technology skills. Based at the IBM Canada Lab in Toronto, he specializes in developing instructional solutions for AI, Data Science, Cloud Computing, and Cybersecurity. His impact on technology education is evidenced through his role as architect of numerous IBM Professional Certificates and instructor for over 35 online courses, including popular offerings like "What is Data Science?", "Introduction to Cloud Computing," and "Introduction to Artificial Intelligence (AI)." His courses have reached hundreds of thousands of learners worldwide, with "What is Data Science?" alone enrolling over 638,000 students. His recent work includes developing new Generative AI courses and career guidance content for IBM's Professional Certificate programs, demonstrating his ongoing commitment to preparing learners for emerging technology careers
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