Ratings and Reviews for Python Project: Software Engineering and Image Manipulation

Not really connected to the rest of the specialization. Overall quite disappointing finish.

Very effective course

There is enough other feedback that goes into detail about what is wrong with this course. There is a lot. It really is a great shame to end this very helpful specialisation on such a low note, but it is what it is. The reason I am giving 2 stars is that the assignment at the end does challenge your thinking quite a lot and helps develop a better understanding for how real world Python projects look like. Again, that's the ASSIGNMENT. The COURSE, which is supposed to help, teach and guide you, is basically useless.

Pro: Jupyter Notebook is a helpful Python interpreter, but we would have benefited from using that at the beginning of the program. The final projects were fun and challenging! Con: This course was released prematurely. Throughout the initial lectures there are several spelling errors on the terminal commands provided. Additionally, throughout this final course, there were missing instructions on how to install things like: Jupyter Notebook, Teseract library, ipywidgets library, coremltools, kraken, and ipywebrtc. Though Jupyter is a great platform, Introducing a new platform after the previous 4 courses having never used Jupiter was a poor choice and left the students to learn entirely new software and set it up - something that should have occurred during the first course. Week 1 requirements were to upload both the image and code, but the coursera software only allowed one file to be uploaded. No instructions on installing dependancies for Jupyter such as to download as PDF even though the upload instructions requested PDF. Overall, poor guidance and instructions with Week 1 assignment. Several “bugs” are noted in Week 3 of the forum as if this is an appropriate fix to the course. Note that courses 1-4 did not require all these “bugs” to be posted in the forum. This is a lack of preparedness and professionally that unfortunately reflects poorly on the whole program, despite the first 4 courses not having such a problem. Module 3 Optional did not work resulting in error: “UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x104228270>”

This course is a complete divergence from the Python for Everybody course and the 4 courses in this specialization. Wasting time digging through pillow etc documentation. Incredibly poor way to start the last course of the Python 3 specialization - unless one is into image manipulation which I am not. The goal for me was to learn python and apply to real world data issues such as forecasting. Modules like numpy would have been much more applicable to work through. I will be taking the data science specialization from another provider (IBM or Stanford (alma mater)) and do not plan to take another course from University of Michigan due to this last course being so poorly administered. The gym analogy was poor excuse for not taking the time to put together more suitable assignments. Such a shame because the first 8 courses were fine.

Abysmal. Total abomination. Zero instruction. Extremely frustrating and major let down if you've been through courses 1-4 of the specialization. If getting the Specialization Certificate is very important to you, there are resources online that you can leverage to complete the project but that is done largely at the expense of any real learning, so I really hope UofM comes up with an alternative final project that is more consistent with the level of expertise attained in courses 1-5 (maybe something on implementing classic algorithms?).

With all due respect this is the worst course I have taken in any online learning platforms. The "teaching" was abysmal if it could even be described as teaching. It's so disappointing considering the other four courses in the specialization were amazing and enjoyable. The only motivation I had for completing this course was for the certificate, whereas the motivation I had for the other courses was to learn.

Compared to the first 4 courses of this specialization, which are excellent, this one is a disaster. The organization is poor. Installation instructions are full of errata and prone to conflicts in a variety of environments. This leads to frustrated students and teaching staff, who are losing their professional tone in the forums. I get it, I also would not want to be troubleshooting massive multi-library installations for a variety of OSs for however-many-students Coursera hosts. Figuring out "what to do next" requires excessive guesswork and assumption. For instance, simply downloading and moving the lecture's .ipynb files to your local environment is only _alluded to briefly, in an optional video, without ever showing it done on screen_. The course then proceeds into an unrelated lecture. Feels very disconnected and jarring. The lectures are poor. They consist of the professor talking into the camera with no accompanying materials, and again a lack of clear direction. A concrete example: the professor talks through navigating to /usr/lib/python/site-packages/PIL/Image.py file and opening it in a text editor, all _without showing the screen or terminal_, while explicitly spelling out "See-Dee" (cd) and explaining that's how you change directories... What? There are several problems with this. 1) It is NOT an effective teaching technique to talk through such multiple dir/file traversals without showing the terminal, as it's easy to get lost from where the prof is talking about. 2) Even if there is an assumption here that the students are *SO* comfortable/advanced with *nix already that you can just talk them through that many cd's AND opening a text editor without messing up the file, WHY do you feel the need to explain what "cd" and "ls" do as if it's our first time using it? There is a strong and jarring disconnect here that makes it feel like the course was unfinished - as if the prof believed he'd have an onscreen accompaniment that never materialized. BAD. The jump in difficulty from the first 4 courses is huge, but it's largely because so many intermediary steps are ignored entirely or poorly explained. The logical composition of this course is nonsense - simple things are explained while complex things are overlooked. If by design it's _intended_ to provoke solution-searching from the student, then at least let the student know that they're expected to find the solution themselves. Overall I found this really frustrating, and a huge disappointment. Poorly thought-out, poorly executed. I imagine the people actually finishing this course are the ones who are REALLY invested in learning computer vision / these libraries for their own needs, and if you have that motivation, you can give it a try. Otherwise, I see no reason to bang your head against the wall fighting upstream against this course's shortcomings. There are plenty of other resources online for learning python and simpler projects with better documentation, that would be a more natural next step from the previous courses. Again - this does not reflect on courses 1-4 of the specialization, which are very good.

Good course

This course is not worth your time. The first four courses in this series were great. Very thorough, good instruction, an interactive textbook with code that you could experiment on, etc... The courses built on themselves and you felt like your knowledge base expanded as the course went on. This course is none of that. It has almost nothing to do with the material previously presented in the other courses. You're left to search through documentation for libraries and packages with almost no instruction. If you want to learn pillow, tesseract, or opencv, just Google them and start reading. You'll learn more that way than you will taking this course. I was finally able to complete the assignments and pass, and I'm incredibly thankful just to be done with this course, but to be honest I still feel like I don't really understand any of the aforementioned packages at all. I don't understand why this course is so bad and has so little to do with the first four courses. If it hadn't been able to take it for free, I would've felt like I'd been robbed.