nice

good

Good

GOOD

nice

This project showcases the successful development of an AI-powered emotion detection web application using Python, Flask, and IBM Watson NLP. The submission includes all required components—from cloning the repository and building the core emotion detection logic to deploying the application via Flask, handling errors gracefully, and running static code analysis. Each step is well-documented with clear screenshots as evidence. The application appears to function correctly and demonstrates good programming practices, including modularization, unit testing, and clean UI deployment.

The lab sessions felt too guided, with step-by-step instructions that took away the challenge of figuring out the approach and steps on my own. It would be more engaging if they encouraged independent problem-solving. Also, having to submit 8-12 screenshots for the final test was frustrating and time-consuming. A code validation system—like automated tests or file submissions—would be much more efficient. I feel that the overly guided process hinders the overall learning experience and makes it harder to truly understand and retain the material.

"Developing AI ..." is misleading. The course teaches you to call an external function (which may be an AI) and reformat the output. You have to jump the hoops of html, JavaScript and Python. Ask Tai when you have problems, since the console's output is confusing and is hard to tell whether the system is down or you have to act specific way (My biggest problem was closing a terminal and opening a new one, instead of using ctrl-c)

It's ok as a general view but the explanation is very poor, the content is good but the methodology for teaching could be improved, also for some reason i am unable to join the professional certificate of Generative AI Engineering, it says i already purchase the specialization and i'm still following the courses but what happens when i finish, it doesn't show that i am in that specialization it says i am in AI developer instead.

I liked this course content, but I am a bit disappointed about its scope. You won't really “Develop AI Applications with Python and Flask”, instead of that, you will be able to develop a web interface to use a remote IBM's Already-Trained AI model, to evaluate some strings via API.

The dynamics of the course are interesting, especially the peer review, however, the title is overpromising: "Developing AI Applications..." that could be misleading as all you do is a normal application consuming a third-party AI service

There were some technical issues with Theia. Why does it still use Python 2.7? It appears incompatible with ibm_watson 6.1. The technical issues meant that it took substantially more time to complete the project.

Flask was only covered at very high level. But this course gives a bit of detail on Software Development Process. Hands-on Lab were very helpful.

Its a basic level. You can use existing AI feature as a url and can use it your application. Thats it.

The course was interesting, but the Theia lab they use it full of bugs that you have to work through.

need more practice for programming. Directly assigning project is not appreciable.

why i complete course all grade pass but i dont have certication

The final project API link is outdated and can't be used anymore

the online coding platform is not very good to use.

Often unclear. Took much longer than expected to

the AI sound makes it harder

Final lab has some issues.

Phyton kernel not stable.

No sé