The week 4 content is a complete 180 from the earlier content in the IBM Data Analysis Certificate. Spelling errors, poor video quality, incorrect information and exercises requiring you to use commands in Python that will not be introduced until later in the course. Some staff were also unhelpful in the forums; replying to questions about exercises and concerns with only a "Thanks for your feedback". I was very satisfied with the course until this point. Other parts of the course were well done and unfortunately made this one part stick out like a sore thumb.

This was by far the worse course. There is no logic going from one section to the next, the time estimates are way off. New sections should build on the previous sections. Also, the Notebooks simply repeats what's in the videos so why having me do both? Also, even by simply copying/pasting the code from one Notebook to another (to see the results), it took me more than the estimated time. And that copying/pasting is not good practice. I finished this section with sub-standard understanding and retention considering the amount of time (and money) invested.

The videos and quizzes were fine. Some parts of the hands-on labs were ok, the final project was fine. However, the hands-on labs are NOT for beginners. They would start out just fine but then most had a last project that was just ridiculous- using functions and syntax that was not in any of the videos or earlier parts of the lab. It was so frustrating for me and the discussion boards are full of tons of other students with the same frustrations. The earlier courses were good, this course was poorly constructed and executed.

This would perhaps be a great refresher course for people who've learned Python or dabbled in other languages, but for someone new to programming (like myself), the videos aren't very helpful and the labs don't explain programming logic or library purposes very well. Some of the exercises were just repeatedly pressing Shift+Enter to run code cells. I found myself constantly asking ChatGPT for explanations because after Module 3, labs introduced codes abruptly without providing any background. Can't help but feel let down!

unfortunately I'm having to supplement this course with Harvard's EDX CS50 intro python as the content here is thin, rushed, and leaves gaps. It also introduces new characters and syntax inside the practice questions that it doesn't cover in the short "lecture" videos. IMO python should have been introduced right from the start of the Pro Cert and not 4 subjects deep, so by the time you got here you would be more established at with it, and not having to reach into other programs to address shortfalls with instruction here.

Contents are simple and easy to learn. However, It covers basis aspects of Python programming

But I expect more in-depth practical examples and exercises. I think the course should includes more projects. The most confused part is about IBM Watson I personally not quite 100% sure what is the goal to include that platform in this course and moreover what does it actually help the future ai/data engineer or scientists. Because most of the time, I was talked about configurations and stuff which I am doubt it will be helpful!

Very disappointing unfortunately. In the video lessons and tutorials all the examples are far away from the "real world" examples. I didn't have the impression that the learning material helped me prepare for the final assignment. Also the explanations in the tutorial are very vague and misleading and partially using obsolete screenshots that don't match the current naming and navigation. I had the impression that I spent more time dealing with the lacking precision of the descriptions than with writing the actual code

I took this course as part of the Data Analyst Professional Certificate and have never worked with Python before. I thought this would be an easy(ish) introduction to Python, however this course is not for beginners. The first two weeks are easy to follow, but the videos and exercises for the rest of the weeks were too fast and too shallow. I had to supplement this course with one from CodeAcademy to feel comfortable with the material, and I still don't feel that I have a firm grasp of Python, Pandas, or Numpy.

This course was just irritating on so many levels. While it does give you an introduction to Python (again many free tutorials online) some/most of the end section exams have 3 questions which is just crazy. Many questions within the videos appear before you get to the answer in their explanation. I found this frustrating on many levels. The course uses Juptyer notebooks without ever explaining the interface. This is the first Coursera course that really makes the question the quality of the course on here.

It wasn't the best course, mainly because a lot of terms, functions, methods, and technologies were mentioned but not really explained. Instead, we were told to "review the lab for more information". However, the lab simply repeated what the videos shared. It would have been nice if complex concepts like matrices, web scraping and file reading were explained a bit more in-depth along with provide real-world examples. Also if the examples tied to each other in some way. A bit disappointed with this module.

There is a huge gap in the level of difficulty between the code shown in the videos and the ones in the exercises. It would be a big help if the solutions, especially the code which wasn't explained in the lectures, would be explained more in detail or at all. Just providing a reference to another provider (for example w3 schools) is not what I have expected as support from IBM. In that case I could have choosen to take Python courses directly at w3 schools.

I think that this course is getting too much credit for the contact it provides.

It defiantly covers the basics and what you should know in order to get started with Python, however, there are a lot of mistakes throughout the classes and the explanations in the videos are too short. They don’t go deep into the why’s and how’s and for beginners it is so important. I had to go and find Youtube videos in order to really understand everything.

Really a shame...

This course was rife with errors in the quizzes. Tons of grading incorrectly and errors or issues in the questions being asked. Pretty unacceptable when you are supposed to be teaching beginners. I am taking this course as a part of a larger series for a certification, and already have a lot of experience with Python. Pretty disappointing to see such a lack of care from a big name company and someone who has a PhD in data science.

The first few weeks cover Object-Oriented Programming basics pretty well, as I have taken a course in Java before. However, weeks 4 and 5 are somewhat week and jump around in the labs, not explaining many of the code that is being used and don't really use enough examples or teach you exactly how to do certain things. I would have to view the solutions and then assume certain lines did "x" or "y" thing without real explanation.

I'm sad to say that I did not find this course great at all. I've already know Python, I've been working with it for 1 year and I think that all the contents are presented so fast that it will be hard for a beginner to undertand them at all. There are some sections of unexplained code, and also there are some typos on the slides. If you are already familiar with Python (as I am) then this course will be a great refresher.

this python project is way more difficult than the basic python course teaches beforehand. I'm getting completely lost as an entry level in coding. The Certificate for data engineering is supposed to be beginner level as per their page, please if we are meant to learn and finish this project give us more python to learn and practice before, its way to difficult I dont want a pass only by copying and pasting the code.

Extremely low production values. Videos often looked sloppily made, seemed to be narrated by a text to speech program, and had completely unedited and unpunctuated transcripts. Labs seemed ok, though I wish they had more exercises. Running bits of code is not sufficient interaction, especially for the more complex topics, where the labs seemed to completely give up on exercises. That's no way to learn anything.

Videos and therefor transcripts need to be improved "like this" shown on the screen is not acceptable. "Teaching staff" also need to be better as they often said they had no issues and no follow up on why multiple students had the same issue. The listed instructor was nowhere to be found in the discussion forums or the videos. I did still learn a bit which is why I decided to go for 2 stars instead of 1 star.

Structure is good but the quality of tuition and support are both terrible. Teaching is via 1) mpeg videos, with some slides being on-screen for under 2 seconds, and 2) hands-on lab exercises which often require knowledge not taught in the videos. And there are no slides to use for reference, and the teaching staff have a habit of 1) not responding to students' queries or 2) providing irrelevant responses.

This course is not for beginners. Participants should come with a background in programming languages if not also a basic foundation in Python. This course also needs QA review to improve organization of the lessons (some concepts were introduced AFTER referring to them in previous lessons) and further processing (breaking down) of large labs into separate, smaller labs or even smaller concept videos.

Too many problems with the last assignment

1) The code given is insufficient to make the graph. A helpful student posted the extra modules you need to import.

2) Instructions unclear about how to set up bucket. Caused lots of problems for many including myself

3) Type in the assignment says "Submit to IMB Cloud" REALLY , you pay that little attention to spelling you cant' get the course create name right?

Content is great. Speed is a little fast for some chapters so had to slow it down. I have a little bit of background in Python so I could keep up. What I liked was having practice problems in the Lab, but there were some labs were there were no practice questions so we couldn't really test our knowledge. Overall good introductory course, but could have been better with more interactive questions.

The course is good, the contents and the difficulty are fine. As negative points I can say that the tests were blocked (I paid to have the certificate) and I could not finish the course before, even having time to do so I had to wait. Very little or almost no support from both Coursera and the Staff of Teachers in the Forum. No one answered the requests to be able to advance in the course.

The first 3.5 weeks go over basic programming skills like what variables are, conditionals, loops. The last week and half go over briefly using Python in a data science setting, which is just using pandas and numpy. The title of this class is misleading. I figured we'd start doing Python coding from the beginning. Most of the code is already done for you. Disappointing.

I felt like comparing to other courses in 'IBM Data Analyst Professional Certificate' series this one felt short in terms of quality. Quiz questions were blatantly copied from videos, the pace of the course was very quick and hardly comfortable for someone just starting out in Python, and there were hardly any truly practical information besides the very basics of Python.