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Learner Reviews & Feedback for Develop Generative AI Applications: Get Started by IBM

4.6
stars
500 ratings

About the Course

Get ready to power up your resume with the GenAI development skills employers need. During this course you’ll explore core prompt engineering strategies—like in-context learning and chain-of-thought—and create and manage robust prompt templates. Plus, you’ll follow best practices to handle common errors and experiment with different LLMs and configurations to strengthen your outputs. You’ll then dive deeper into LangChain, mastering chains, tools, and agents to create smarter, more responsive applications. Through interactive labs, you’ll build a complete generative AI app using Python that accepts user input and processes it through your backend prompt logic. Plus, you’ll explore web-based interfaces using tools like Flask and Gradio, developing real-time user experiences powered by LLMs. By the end, you’ll have the job-ready skills and demonstrable practical experience employers look for to design and implement full-stack GenAI apps that solve real-world problems. Sound good? Enroll today!...

Top reviews

SS

Aug 25, 2025

Step by Step introduction to concepts with Lab Guide and Summarized Notes and Cheet Sheets to revise the concepts.

TH

Jul 14, 2025

The practice Lab is well designed. Module 3 is somewhat repeated and buggy. But overall, it's nice to join this course

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101 - 104 of 104 Reviews for Develop Generative AI Applications: Get Started

By Adith

•

Sep 23, 2025

Very basic level course, could have been more detailed, but does the job.

By Alexandre C

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Apr 28, 2026

Course is out to date. The theory is still valid, but most of the practical and labs is out to date with libraries and implementation with old version. Would be very helpful if before take the course we know the last programa, course and lesson updates to make a better choice. For example: Some course we can find "Recently updated! February 2026", but most of them we do not know.

By Omar A

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Nov 27, 2025

Most of the code does not work. some models are gives end of lifecycle errors and others plainly do not work. some API keys also does not work either. course content is well structured but the estimated of completion is grossly underestimated i.e. a lab that takes 4 hours to complete marked as a one hour assignment.

By Peio A

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Apr 18, 2026

All the lab exercises are outdated. The llms provided by coursera are not compatible with the environment provided in coursera. Even the solution provided by coursera has errors sometimes. Due to this, I had to reprogram multiple parts of the practices, taking longer than the expected time (1h). As a result, I haven't been able to complete the practices as my schedule passed. I'm working while I learn this course and fixing the inconsistencies of the examples provided by the course just consumes too much time for me and I'm not being able to complete everything on time.