Generative AI: Enhance your Data Analytics Career
IBM · View on Coursera ↗
Taught by IBM Skills Network Team
Data ScienceBusinessPersonal DevelopmentInformation Technology
About the course
This comprehensive course unravels the potential of generative AI in data analytics. The course will provide an in-depth knowledge of the fundamental concepts, models, tools, and generative AI applications regarding the data analytics landscape. In this course, you will examine real-world applications and use generative AI to gain data insights using techniques such as prompts, visualization, storytelling, querying and so on. In addition, you will understand the ethical implications, considera
The dissent
The most-upvoted critical review (8 votes, 1.0★).
“Imagine if the most dry and boring textbook was given to you to read, but instead you had a robotic AI voice reading it to you without taking a breath or actually understanding what it was talking about, and the images were all AI generated with no real relationship to the tools being talked about, no context, background, stories, metaphors, or anything. No teaching understanding, just a regurgitation of technical words, descriptions and summaries.... Thats what this course is. Honestly, the course makers of IBM should get fired, I've taken so many of the courses and they are all the same format and style. I suspect even their reviews are AI generated. I don't know why i keep thinking i should give it a shot. The makers should honestly take some courses on Coursera on learning how to teach, before putting out another AI_generated content farm. This was pretty rough to get through honestly”
Coursera's 4.6 comes from 191 ratings. Of those, 6.8% are 1–2★.
Starisk reads the reviews learners voted most helpful, and weights each by the square root of its votes: a review with 80 upvotes counts about five times one with 2. Unvoted reviews are not skipped out of laziness — by this model they carry no evidence that other students endorsed them.
That measures what the most-endorsed reviews say, not “true quality.” The rating distribution above is the whole population, so you can see the sample next to it.
Reviews read on 23 Oct 2026.Read them on Coursera ↗