This comprehensive Generative AI Training, Evaluation, and Trends course equips you with the skills to build, optimize, and future-proof GenAI systems. Begin by learning how generative models are trained and evaluated using real-world metrics. Explore Retrieval Augmented Generation (RAG) to improve model accuracy by combining external data with LLMs. Progress into key trends shaping GenAI—like scalable architectures, real-time applications, and model transparency—while examining how these advancements apply across industries like healthcare, finance, and education.
Foundations of Generative AI Models
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
3 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Train and evaluate generative AI models using real-world techniques
Apply Retrieval Augmented Generation (RAG) to improve output accuracy
Understand emerging trends in GenAI architecture and deployment
Translate GenAI advancements into practical, industry-ready solutions
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
June 2025
Assessments
6 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
There are 2 modules in this course
Build a strong foundation in Generative AI with this module covering its importance, real-world impact, and core concepts. Understand why GenAI matters through relatable analogies and explore key model types, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformer-based models. Ideal for beginners starting their GenAI journey.
What's included
8 videos1 reading3 assignments
Explore how Generative AI models are trained, evaluated, and enhanced using Retrieval Augmented Generation (RAG). Learn the key steps in model training, techniques to assess model quality, and understand how RAG improves output accuracy by combining retrieval and generation. Discover emerging trends shaping the future of GenAI and gain insights into evolving industry applications.
What's included
6 videos3 assignments
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Instructor
Offered by
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
New to Machine Learning? Start here.
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
Generative AI models are algorithms that create new content such as text, images, or code; based on patterns learned from data. Common types include GANs, VAEs, and transformer-based models like GPT.
Foundation models are large-scale AI models trained on vast, diverse datasets and adaptable across a wide range of tasks. Examples include GPT, BERT, and CLIP.
The four models of AI are reactive machines, limited memory, theory of mind, and self-aware AI; representing increasing levels of complexity and cognitive capabilities.
More questions
Financial aid available,