tks

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hmm

yes

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5

Informative, but outdated when it comes to the new tools. They don't mention the 'best' tools, but rather the 'best tools in the ecosystem of IBM/Microsoft'. For example there is no mention of Claude etc. as code tools. Its a simple generative search away to find which tools are best, so there is no need to try to limit people to IBM alone, even if the course is created by them. Also AI generated 'podcasts' is pretty annoying - it's a summary, not a podcast.

Good beginner introductory course, however my one criticism is there is a lot of references and questions comparing specific AI models or applications. The landscape and AI ecosystem is evolving so rapidly many of the models reference have advanced in capabilities since the writing of this course so the differentiations or comparisons between capabilities is not nearly as pronounced.

J'aurai aimé avoir un listing des AI par catégories, un peu comme le glossaire, et peut--être un exercice ou projet que je pourrai mettre dans le portefolio, et pour moi je suis plus à l'aise en français, si la partie audio pouvait être en français aussi sinon merci beaucoup vous avez été génial, c'est juste un peu de critique constructive pour tjr continuer à évoluer

The first third of the full course—the Introduction and Applications module—is quite broad. It’s a good starting point for people who are completely new to generative AI. However, if you’ve already worked with tools like ChatGPT, generated images, or done some coding with AI, this section will mostly feel like a refresher of what you already know.

This course is an excellent starting point for anyone curious about generative AI and its practical use cases. While not highly technical, it provides solid conceptual grounding and access to hands-on practice through IBM tools. Ideal for professionals or students looking to understand the possibilities of this fast-growing field.