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Learner Reviews & Feedback for Generative AI with Large Language Models by DeepLearning.AI

4.8
stars
2,942 ratings

About the Course

In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications. By taking this course, you'll learn to: - Deeply understand generative AI, describing the key steps in a typical LLM-based generative AI lifecycle, from data gathering and model selection, to performance evaluation and deployment - Describe in detail the transformer architecture that powers LLMs, how they’re trained, and how fine-tuning enables LLMs to be adapted to a variety of specific use cases - Use empirical scaling laws to optimize the model's objective function across dataset size, compute budget, and inference requirements - Apply state-of-the art training, tuning, inference, tools, and deployment methods to maximize the performance of models within the specific constraints of your project - Discuss the challenges and opportunities that generative AI creates for businesses after hearing stories from industry researchers and practitioners Developers who have a good foundational understanding of how LLMs work, as well the best practices behind training and deploying them, will be able to make good decisions for their companies and more quickly build working prototypes. This course will support learners in building practical intuition about how to best utilize this exciting new technology. This is an intermediate course, so you should have some experience coding in Python to get the most out of it. You should also be familiar with the basics of machine learning, such as supervised and unsupervised learning, loss functions, and splitting data into training, validation, and test sets. If you have taken the Machine Learning Specialization or Deep Learning Specialization from DeepLearning.AI, you’ll be ready to take this course and dive deeper into the fundamentals of generative AI....

Top reviews

OK

Jan 28, 2024

Easily a five star course. You will get a combination of overview of advanced topics and in depth explanation of all necessary concepts. One of the best in this domain. Good work. Thank you teachers!

C

Jul 10, 2023

A very good course covering many different areas, from use cases, to the mathematical underpinnings and the societal impacts. And having the labs to actually get to play around with the algorithms.

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226 - 250 of 740 Reviews for Generative AI with Large Language Models

By Javier A

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Aug 18, 2023

An excellent introduction to LLMs. What I liked the most are the weekly resources... which include the most relevant papers.

By Rodolphe B

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Sep 18, 2024

Very good course. I just wish that a lab will also be present in the last part to see PAL, React and agents in python code.

By Emerald B

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Nov 15, 2023

Provided useful up-to-date information concisely. It also gave a taste of practical hands-on labs that can be fiddled with.

By Fraser S

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May 18, 2024

This is an excellent class. The lecture material is excellent, as are the labs. Its worth buying to get the lab access.

By Vilen A

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Mar 18, 2024

Great intro into the generative AI with Jupyter notebooks that allow you to practice and experiment with model parameters

By Venkatesan K

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Oct 5, 2023

Fantastic intro(also a fair share of advanced concepts) to LLMs. Gained loads of knowledge on how LLMs work and deployed.

By Erdi K

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Nov 12, 2024

I think the content is more than enough to pass a high level LLM interview with fair amount of coding projects also plus

By Hansaka R

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Feb 1, 2024

This course helps me to understand lot of things about LLMs and how it is works on applications and works on AWS labs. .

By sateehs p

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Jan 23, 2024

very detailed and useful course - labs are useful - good start for any one who is willing to join the Gen AI revolution

By Julien H

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Oct 12, 2023

The course provides an excellent overview of LLMs, and is a perfect way to start using them to develop new applications.

By Divya V

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Aug 31, 2023

Course contents are highly informative and mentions recent publications in the domain. I liked. Many thanks to the team!

By Martin P

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Jul 16, 2023

A fantastic course that provides a broad spectrum of the current state-of-play in GenAI. I highly recommend this course.

By Don M P K

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Jul 5, 2023

This is the best course out there at the moment . kudo to DeepLearning .ai and Amazon team for creating this course .

By Pablo S

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Jul 5, 2023

Excelent content, including diverse methods and use examples. I will only suggest to add coding exercises to the labs

By Rajesh R

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Apr 1, 2024

Extremely informative, useful and well taught course, thanks for DLAI for offering this course in coursera platform.

By Shahzad A A

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Oct 4, 2023

It is an in-depth course for someone who wants to learn what is generative AI and how to build applications with it.

By sriniprasanna77

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Feb 5, 2024

Detailed enough to understand the various components, approaches, methodologies that power the functioning of LLMs.

By Tom S

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Jul 25, 2023

A great survey of key issues and techniques. The reading lists are launching points to understanding these topics.

By Paramdeep S

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Jul 23, 2023

A great course that takes you from the very basics to complete the full Generative AI journey. Highly recommended.

By Ashok S

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Jul 17, 2023

This one truly nails the concepts of LLMs and how they can chained in the overall lifecycle of Gen AI Driven Dev..

By Akshay K G

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Aug 8, 2024

Really comprehensive and structured curriculum covering all the topics along with hands-on labs. I learnt a lot.

By sunil A

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Jan 27, 2024

Very good overview of all the steps in the Generative AI pipeline. Thanks for the lab and the reading material.

By Stefania B

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Jan 3, 2024

Very interesting content and well structured! I suggest this class to everyone interested in GenAI foundations.

By Rithesh K

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Sep 25, 2023

Very well organized course that provides in-depth foundational knowledge of LLM's and LLM powered applications.

By Rupin D

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Nov 12, 2024

The course is excellent. However, it would be beneficial to include hands-on training in labs for RAG as well.