Kevin Katz

Overall, I found the course thorough and engaging. Colt's obvious Pythonic chops should also be commended. I can say that I started with zero knowledge of openai APIs and now have a good understanding of text, image and audio workflows. Note: I'm taking this course as part of my firm's education path for AI engineering. I started in late September 2025 and completed today, November 5th 2025. I took my time with nearly all the labs, often expanding on (and fixing others for my environment which does have its challenges with corporate firewalls). Regarding the sample code, staying on the positive side, they were extremely helpful in getting me hands on with ai workflows in Python. I am an advance C#/C++ developer and intermediate in Python. Given the rapidly changing AI landscape at the time this course was created it is understandable that there would be some impedance mismatches at times. I never worked with the original codebase, but only the updated one. I learned a ton. The sections on embedding I found to be the most useful given the interest in RAG. That was something I worked through in detail with the labs. On the 'things to improve' side of the ledger, while I love the wonky stuff, and went there with you on aspects (memoize, retry) etc... I'm not sure that tgese demonstrations of Python mastery contributes ultimately to the end goal of focusing on the specifics of the API. Just a note, while the videos may be 13 hours or so - my lab work took probably 25-30 hours to do justice to the course. Yes, you said it was optional but really how can you learn without getting into the code! Overall you were very engaging, skillful and I am much further along than I was before taking the course. Note: My previous experience with AI were basic prompting courses and a Coursera course in AWS Sagemaker call Generative AI with AWS etc..
- Review by Joe Regan on Mastering OpenAI Python APIs: Unleash ChatGPT and GPT4