糖心vlog官网观看

Chevron Left
Back to Advanced Prompt Engineering for Everyone

Learner Reviews & Feedback for Advanced Prompt Engineering for Everyone by Vanderbilt University

4.8
stars
306 ratings

About the Course

Unlock the full potential of generative AI and become a master of prompt engineering. Dive deeper into how you can use In-context Learning to build better and more reliable prompts. See how Retrieval Augmented Generation (RAG) works and what can go wrong that you can counteract with fact-checkable prompt formats. Overcome your struggles in getting the right output from generative AI models with template-based output formats to achieve precision in your interactions with AI models. Tap into powerful AI capabilities for tasks ranging from social media comment analysis to survey results interpretation and beyond. This course will empower you with the skills needed to build exceptional prompts, using simple techniques, such as preference-driven refinement, and become and expert in leveraging generative AI for productivity and creativity. What You Will Learn: In-Context Learning: Understand how to provide context within prompts to guide AI models towards more accurate and relevant outputs. Learn techniques to embed contextual information that enhances the model鈥檚 understanding and performance. Retrieval Augmented Generation (RAG): Explore how to integrate retrieval systems with generative models to provide more precise and informed responses. This module covers the mechanisms to combine the strengths of both retrieval and generation. Template Pattern and Examples: Master the art of crafting template-based prompts to achieve consistent and desired outputs. Learn how to tell generative AI to fit its output into your format and overcome struggles with getting exactly what you want. Tapping Into AI Capabilities for Everyday Use: Delve into practical applications such as analyzing social media comments, interpreting survey results, and other everyday tasks where generative AI can make a significant impact. Gain hands-on experience with real-world examples. Building Great Prompts: Discover simple methods for constructing effective prompts. Learn how preference-driven refinement can elevate your prompt engineering skills, ensuring that outputs meet your exact needs and preferences....

Top reviews

AL

Aug 29, 2024

This is a must-take course if you are keen in advancing your prompt engineering knowledge and skillset gameplan. It gets better as Dr Jules White spins deeper iterations on prompt engineering.

RM

Aug 22, 2024

It helped me better understand in-context learning and working with unformatted text data. I was able to start using the techniques immediately. Jules White is a very pragmatic instructor.

Filter by:

51 - 75 of 81 Reviews for Advanced Prompt Engineering for Everyone

By Thiago G

鈥�

May 29, 2025

Everything learned here is super usefull!

By Valerie S

鈥�

May 10, 2025

Just excellent!!!! I can only recommend.

By Luis D G

鈥�

Nov 26, 2024

Good practical approaches to using AI

By robert f

鈥�

Mar 14, 2025

Well explained and always helpful

By Theo P

鈥�

Jan 11, 2025

Really enjoyed doing this course.

By Jodi B

鈥�

Jan 8, 2025

Very informative! Thank you!

By Aramide A

鈥�

Dec 8, 2024

Excellent course. Empowering!

By Kelly H

鈥�

Nov 23, 2024

once again a fabulous course

By Marc S

鈥�

Mar 27, 2025

Thanks professor White!

By Dean M

鈥�

Sep 3, 2024

Nice pace and examples.

By Manohar P N

鈥�

Nov 29, 2024

Good for the beginners

By Dan E

鈥�

Oct 27, 2024

Excellent Course.

By Kevin1

鈥�

Jun 2, 2025

Excellent course

By Yahya S

鈥�

Apr 24, 2025

Great Instructor

By Nazariy K

鈥�

Feb 17, 2025

very good course

By Thomas S

鈥�

Apr 18, 2025

Great course

By Todd H

鈥�

Apr 29, 2025

Excellent!

By Fina A

鈥�

Mar 10, 2025

very good

By Kage C

鈥�

Jun 12, 2025

awasmoe

By Gracie K

鈥�

Jun 4, 2025

wow!

By Rina M

鈥�

Apr 20, 2025

good

By Melisa 脟

鈥�

Sep 16, 2024

cool

By Maratov D M

鈥�

Apr 25, 2025

ok

By Jeff Y

鈥�

Aug 12, 2024

The information presented on prompt components and markdown is very helpful.

By KONSTANTINOS G

鈥�

Sep 16, 2024

螛伪 萎胃蔚位伪 谓伪 蔚委谓伪喂 渭蔚蟿伪蠁蟻伪蟽渭苇谓慰 蟽蟿伪 螘位位畏谓喂魏维