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.

The course was not designed and taught properly. Although python language is very interesting, but this course presented it in a very boring way. I couldn't understand the bigger picture in this course and its relevance to AI. Practice assignments were not enough. Compared to other IBM courses in this certification, this course was definitely not of the standard.

Für Anfänger ist der Kurs zum Teil schwer zu verstehen. Es wird nicht einmal erklärt, dass die Einrückungen bedeutsam sind.

In den Videos wird nicht klar unterschieden, was ist Programmcode, was ist die Ausgabe. Variablen heißen ähnlich wie die definierten Objekte, so das es nicht immer eindeutig erkennbar ist. Beispiele sind oft nicht einfach nachzuvollziehen.

I feel overwhelmed by the amount of information presented in the course and frustrated that you don't really get to practice what you learn. Most of the labs (if they load) already have the code entered and you just run it. You can play with it if you want, but I don't feel like I really retained all the coding and syntax that was presented.

There are simpler ways to present information. The narrative was extremely fast paced. I found myself having to slow the narration down quite a bit. The course was not for me and I will seek to learn Python through a different means. I do appreciate the limitless opportunities to test and run your code, which is why I gave two stars.

Course is full of typos, random words in random places and other kinds of errors. I wish the instructors would at least once go through the course to see what a mess it is. I really am grateful but this course was a constant headache. Not because it was difficult but because of all the mistakes. Thanks and please fix it !

Weeks three and four need a major overhaul in their examples and exercises. The examples themselves are not translatable to what the student is expected to do in the exercises. For example, at one point the module teaches you how to create circles and rectangles. When you get into the exercise, it is building a database.

I am disappointed with this course and especially with the APIs part and the use of IBM Watson Studio. It is very poorly explained, we talk about predicting house prices and then we work on US economy. It deserves to be reworked. I wasted a lot of time figuring out what is required and not getting started with python