EdX

Models and Platforms for Generative AI (edX)

Offered by IBM,
Models and Platforms for Generative AI (edX)

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.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

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

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

AI Skills for Engineers: Data Engineering and Data Pipelines (edX) EdX
Delft University of Technology,DelftX

AI Skills for Engineers: Data Engineering and Data Pipelines (edX)

Good data is central to effective AI applications. This course teaches the basics of data for AI, covering what data is needed, how to extract data from existing databases and basic data skills including setup of a Python notebook environment, basic data exploration and simple data visualizations.

Self Paced
Self-Paced
Applied Deep Learning Capstone Project (edX) EdX
IBM

Applied Deep Learning Capstone Project (edX)

In this capstone project, you will apply your newly acquired deep learning knowledge and expertise to a real world challenge. In this capstone project, you'll use a Deep Learning library of your choice to develop, train, and test a Deep Learning model. Load and preprocess data for a real problem, build the model and then validate it.

Self Paced
Self-Paced
Humanitarian Action in the Digital Age (edX) EdX
École Polytechnique Fédérale de Lausanne,EPFLx

Humanitarian Action in the Digital Age (edX)

The first MOOC about responsible use of technology for humanitarians. Learn about technology and identify risks and opportunities when designing digital solutions. As humanitarian practitioner, you are interested in technology but you feel it should be used more responsibly? You are worried people tend to jump on opportunities without properly considering risks? This MOOC is for you!

Self Paced
Self-Paced
Ethics in AI Design (edX) EdX
Delft University of Technology,DelftX

Ethics in AI Design (edX)

Learn how to incorporate ethics into the development and implementation of AI systems. AI systems have a great potential to improve society, across a wide range of applications. The challenge is to do so responsibly. AI systems can lead to discrimination, loss of human control and a lack of explainability, to name a few ethical dilemmas they may present. Because of the great impact that AI and Machine Learning has (e.g. ChatGPT by OpenAI, or the use of ML for medical diagnoses), we need to ensure that we design and use them in a way that meets ethical standards.

Self Paced
Self-Paced
AI skills: Introduction to Unsupervised, Deep and Reinforcement Learning (edX) EdX
Delft University of Technology,DelftX

AI skills: Introduction to Unsupervised, Deep and Reinforcement Learning (edX)

Learn the fundamentals and principal AI concepts about clustering, dimensionality reduction, reinforcement learning and deep learning to solve real-life problems. In this course you will learn the basics of several machine learning topics to help you solve real life challenges. Unsupervised learning techniques such as clustering and dimensionality reduction are useful to make sense of large and/or high dimensional datasets that are not annotated. Deep learning is a supervised learning technique that is useful to train neural networks to solve more complicated classification and regression tasks. Finally, reinforcement learning techniques can be used to train AI agents that interact with an environment.

Self Paced
Self-Paced
AI in Practice: Preparing for AI (edX) EdX
Delft University of Technology,DelftX

AI in Practice: Preparing for AI (edX)

Learn to recognize and understand the implications of Artificial Intelligence for organizations, and the importance of compliance and ethics when AI is applied in practice. This course is not about difficult algorithms and complex programming; it is a course for anyone interested in learning about the benefits and implications of AI when applied in practical settings.

Self Paced
Self-Paced
Gobernanza de datos personales en la era digital (edX) EdX
The Pontificia Universidad Javeriana,JaverianaX

Gobernanza de datos personales en la era digital (edX)

Law

Aprende qué es la gobernanza de datos personales y desarrolla habilidades para diseñar e implementar leyes y políticas públicas en materia de datos personales en la era digital. Este curso en línea te ayudará a comprender qué es la gobernanza de datos, los criterios que deben tener en cuenta quienes formulan política públicas al momento de redactar o desarrollar leyes, regulaciones o políticas en materia de protección de datos y privacidad, así como aspectos prácticos de los programas de gobernanza de datos.

Self Paced
Self-Paced