Instructor was not good, I had to search for everything in order to do the projects.

and the course was fast paced, not like the previous 4 courses

Not very well maintained over time. Small errors here and there that make it an unnecessary challenge to complete the course.

Good experience of coding But the videos are too fast to understand overall good course

I woud prefer a course with more hours, to have the codes explained in a detailed pace.

Courses 1 to 4 of this were very well made and structured. This one not so much.

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in of the assignement is terrible.

The content is good, the way the training organized needs to be improved.

watch out for the the last course!!

rest is totally amazing!!

Explanation was not so good like other courses

Bad assignment arrangements and design

not as good as the previous courses.

Not much Detailed

its a bit fast

thanks

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Look, I get that a lot of learning has to be self-directed, and you do learn a lot of trial and error and figuring stuff out by yourself. But at the same time, I do feel that the whole point of designing a course is to direct one's learning in a more guided manner that enables for more EFFICIENT and QUICKER learning. Having completed the first four courses in this specialisation, which were amazing in that aspect, this final course was a MASSIVE letdown. Honestly, I don't see much of a difference if I were to attempt this project directly through github or something and bypassing the course entirely. (From the perspective of someone who knew almost nothing about coding/python prior to the specialization)

Considering the step up from the previous courses, Week 1 was horrible - basically felt like everything was being glossed over, making the entire learning process terribly rough and I ended up spending most of my time googling stuff to figure out what was going on . The lack of teaching honestly made figuring out the week's assignment way harder than the final assignment. Week 2 and 3 saw some improvement, but then goodness me the final assignment submission process was an absolute disgrace - being expected to paste our code into that text box and the peer reviewer to run the code by ourselves ... especially knowing how long the code takes to run .... honestly felt like there was a huge lack of effort on the course designers part.

This course was a real disappointment when compared with the other courses in the Python 3 Programming specialisation. Steve and Paul were EXCELLENT in the first 4 courses, building concepts up slowly and assigning challenging but manageable final assignments that integrated everything learnt prior. This capstone on the other hand had a complete 180 in terms of pedagogy. If the aim was to teach students to learn how to dig through messy documentation, fiddle with libraries and dependencies, and read page after page of stackoverflow forums, then a simple project requiring us to find a library and explain several features would’ve sufficed. Instead, we got three libraries thrown at us with nary an explanation of how to use them. I’m not talking about simply reusing code that has already been constructed by Christopher, but rather, going through analytical skills of how to deconstruct any library and work out the functions. I’ll still recommend the course, but the final capstone does leave a bad taste. I felt like I was tracking to hack together some abomination, instead of purposefully constructing a tool step by step. A shame given that the incremental style of development was emphasised by Steve and Paul a lot. Here, I was adding lines of code without care as to what they did, just in the hopes that it would give me the outputs needed to pass.

On course deign: this course was arranged in a way that is so different from the previous 4 courses of this specialisation. I am using a 11" Mac, and in the lecture video, code blocks would not zoomed, and if I turned on subtitles, that area would cover what the instructor was coding, that has really caused me a headache, and when the instructor was demonstrating, it like he was just following a fixed speed to read out a script, but not really showing how to code... then what's the point of setting up this video lecture? I could have just read the Jupyter module.. And for the "setting up Jupyter Notebook" video, the instructions are not applicable to my machine and the terminal commands were only shown on the video. I do appreciate the doing the projects and how they took us to a greater knowledge depth and a more real-world situation, I just hope they could have planned the communications in a more mindful way. I know technical issues are related to other dependencies, which is somehow more understandable, but I think the course staff should really focus on improving the overall content design and presentation.

I took this class because it was part of the Python 3 specialization (the last course actually).

The main advantage of the course is the introduction to Jupyter Notebooks. A big plus for me.

But the content is very (too) specific and quite in contrast with the broader applications of the 1st 4 classes in the specialization cycle. And if the idea was to deepdive in a real world application, I get it, but then it would probably have needed to be something a bit more interesting and useful (like pyplot or django).

Finally, and that's the big drawback, the end project was a nightmare, an absolute waste of time. The Coursera platform could simply not handle the required homework. It would run slow (if ever), not accept anything but the raw code (all messed up). The forum is crammed with people asking for a review of their submission, without proper moderation, drowning the more interesting content.

Fortunately I found a work around by running everything locally and posting the Notebook on my own site. But there should have been much better coordination between UMich and Coursera on the submission format.

This course is too ambitious in trying to achieve what it expects of a novice programmer in 3 weeks. PILLOW, TESSERACT and OPENCV are good libraries but will easily take a novice programmer even with some experience in programming at least 3 months to learn and apply what's used. The poor quality of lecture and pedagogy in this course adds on to the woe of students like me trying to figure out what is exactly being taught in this course and how to apply this in the real world. Any student taking this course will emerge feeling as if we don't have good grasp of the concepts and topics which is a shame given the amount of time, and not to mention money spent.

Although the course had very interesting material, the projects were much more difficult than the previous courses. The lectures were quick and confusing and did not provide enough information to complete the assignments. The project files were huge and took between 15 minutes and over an hour for each run of the assignment. Smaller project files could have been used to accomplish the same goals. If this was not the last course in the specialization, I would have given up just because how long to took to run the project files.

Not terrible, but enrolling in this course is a bit like gambling: either you win a lot, or you lose a lot. The assignments are VERY hard, in relation to the other assignments in the Specialization, and since they only allow you to input one file as a submission you have to run TWO huge programs on zipfiles, instead of just being able to run on one zipfile, and then do the other zipfile later. But, as I said, if you ARE able to do the course, you will gain a lot of experience. Choose wisely.

I Think this course is not for beginners,besides i'am a beginner i had very tough time to solve the assignments and the instructor had taught so fast like newsreader.

if you really want to learn the pillow,tesseract and opencv don't take this course.This instructor had another course applied data science with python.

Finally as a beginner i felt very challenged and i've done some digging on the modules and the libraries on my own and solved the problems

Not very relevant to the use of Python especially in the context of finishing up a specialization. The other courses are excellent and this good if the reason you are learning python is to do OCR or ultimately computer vision. Would have been better if the 'exploration of libraries' and research were applied to multiple domain areas of python use such as mashups, workflow orchestration, data analysis, etc....

This course was the final course of the Python 3 Programming Specialisation and it was a frustrating experience overall. Compared to the first four parts (which were great experiences), this one doesn't fit in at all. It's a bit mind blowing how different it is from the first 4 parts actually.

The subject is interesting though.