May 10, 2020
The course had helped in understanding the concepts of NumPy and pandas. The assignments were so helpful to apply these concepts which provide an in-depth understanding of the Numpy as well as pandans
Dec 10, 2017
Wow, this was amazing. Learned a lot (mostly thanks to stack overflow) but the course also opened my eyes to all the possibilities available out there and I feel like i'm only scratching the surface!
By Bas R•
Feb 10, 2020
Topics covered are interesting as next steps when you have some basic programming skills in Python. However, the introduction and explanation of new concepts feel very rushed; a one minute video on map(), then lambda with a quick exercise without further explanation, followed by list comprehension at the same pace. I often found myself stopping the videos and googling for further explanation to understand what is really going on. If instructors feel that such concepts should be familiar to someone participating in the course, then I'd recommend not covering them at all, rather than rapidly rushing through.
By Qiang L•
Mar 17, 2020
I think most of the people mentioned that in the review. There is a HUGE gap between the lecture and the assignment. I am a beginner level of python and know some programming, and I feel really hard to work with the assignment, most of the content in assignment does not cover in lecture. Basically you need to google almost everything you need to finish every assignment. I have been struggling with that since assignment 2. SO what's the point to take a course, why not I just do the assignment directly and google everything. I hope you can change the content and adjust the conection between material and assignment. If you still want do keep the same assignment, try to give more detail in the lecture or have some examples. At least provide some prerequisite course before further into this course.
By Eklavya S•
Aug 05, 2018
This course makes you give up on data science and MOOCs.
Seriously, the content is poorly presented he keeps on speaking , telling 2-3 lines about a function and so on.
I highly recommend stay away from this pathetic specialization.
By Tural H•
Mar 05, 2020
Very fast pace, no clarity of the scope and poor leacturing
Feb 12, 2019
Not nearly enough reference content in lectures. It needs to be made clear students coming from the Python for Everybody course (other Umich course) has a book which I was used to referencing for all of my questions (the class was pretty well self contained and did not require much looking up of concepts). I tried to learn this class the same way I did for the previous one and that totally did not work - I spent wayyyy too much time on my first pandas assignment thinking all of the answers were in lecture/notes. The lecture and notes were very very scant and not well explanative about data structures that are very complicated. Please either write a book or make it more clear how students should learn. Yes, the teacher tells us about stackover flow but I didn't know he was implying for us to use those resources. He should say something like "we don't offer a book with this course so use online resources" and not tip toe around the topic because people paid money to learn so take responsibility and make these changes please. I passed but it was very frustrating at first.
By Bruno S P P•
Jul 14, 2020
My background: Industrial Engineer with a decent programming background (including Python), but rusty with statistics.
My review: The instructors clearly know what they are talking about and explains useful concepts. However, the videos are very short, and some concepts feels rushed. The assignments are pretty challenging, which is a nice thing. The last one in particular is very nice and don't feel fabricated - you actually test an interesting hypothesis based on some data you have to extract and manipulate. To be able to finish the assigments, I had to use Google a lot. It kinda felt like cheating, but the course is pretty clear that you should look in the documentations and ask questions on Stack Overflow.
Include more exercises to practice what was taught in the videos.
Include a solution for each assignment - some questions I got it right, but I am sure my answer was not the most efficient or "pandorable" one. It would be nice to have a benchmark to compare after we pass the assignemnts.
By Kelam G•
Jan 17, 2019
It was informative but i felt the assignment part needed more clarification. I faced the problem that even though my solutions were right the autograder gave me lesser marks. I figured out that we must not print to the console. If that was clearly mentioned life would be easier.
By Trish P•
Apr 29, 2019
Solid course. I definitely would not recommend it to someone who doesn't have advanced beginner to intermediate python knowledge, though - while it does a good job at a review level for the necessary python, it really moves through the code details quite quickly.
By Marcel K•
Apr 19, 2019
It would be nice if Coursera could update the Python environment used for the exercises and assignments to something recent. The version they're using (0.19) is fairly old. Every single assignment that I had running against 0.24 had to be altered in some way to work for 0.19.
By Michael P R•
Mar 21, 2019
Good course overall, but more material is required to be learned outside of this class for the required assignments than what is actually taught in the class by a very wide margin
By Aaron B•
Mar 20, 2019
Really appreciate this course. Got me started in Python, Pandas, and Jupyter. First week felt like magic. I am giving it a low score because the assignment questions were so ambiguous that it required constant resubmits an scouring the forums. The ratio of learning of course content to required Stack Overflow internet research was way off balance.
I learned a lot but was extremely frustrated and burned a lot of time it what I felt was all the wrong places.
Still grateful for this opportunity. I think the questions can be better explained and tightened up.
May 25, 2020
The assignments are fine, they are pretty tedious at times, but it is this kind of situations that forces me to self taught myself. Something really bad about this course is the lectures. They assume we know everything, I wouldn't be able to follow if i haven't done python in data analysis before, g, so they go fast and doesn't explain how everything/every function works. But if they assume we know everything, there is no need for the lecture videos. Just give us the assignments and just ask us to look at stackoverflow. The videos are 90% useless.
By Daniel A•
Aug 20, 2018
This is not really a course. 2h of lectures in total. I have been in longer one-day university lectures. You have to attend other courses in order to be able to complete the assignments because 90% of what they ask is not in the lectures. This is a compilation of exercises, not a course.
On the other hand, the assignments and exercises are OK, that's why I gave it 2 stars.
By Marc B•
Jan 11, 2019
The assignments are good practice, but the course teaches you nearly nothing. You have to do your own research to figure out how to do them.
There are some very useful Mentors on the forums to help the assignments, and if it were not for them, this course would be unbearably frustrating and useless.
By Michael B•
Mar 03, 2020
Video lessons go way too fast and don't actually try to teach you anything. If you're already a wiz at using Python to do data analysis, then you could certainly keep up, but then you wouldn't need the course in the first place. Very poorly paced.
By Mahmoud F•
Mar 04, 2020
the course speed is very highand assuming high level of knoweldg
By Muhammad A•
Apr 19, 2020
I would not recommend this course at all. This is for a number of reasons.
The lectures are not really lectures, they are more of a narration of someone else writing code on screen, the intructor just whizzes through what's happening without giving any proper explanation (I cannot stress this enough). The limited explanation provided is just on what's happening on the screen rather than why we're doing it this way compared to any other way. There is also not enough guidance given in the lectures but told to just figure it out and go post on Stack Overflow. Anyone familiar with Stack Overflow should know, they *really* do not like beginners posting repetitive questions - so I find that advice from the instructor really odd.
The courses makes use of Numpy, but gives zero explanation on what Numpy is and why we use it. It just dives into it by using Numpy arrays and expects you to either magically understand it or go learn what/why Numpy, from someone else.
Speaking about assignments, a lot of the excercises require you to do something which hasn't been covered in the sessions at all. I understand giving a challene in assignments, but I would much rather prefer those challenges be related to things taught or from resources given / pointed to. But, unfortunately, you have to figure a lot out on your own and the videos are of no help.
It also doesn't help that the assignment feedback is very lacking. The grader also does not tell you what answer it expects, so you have no way of knowing how far off your answer is.
This is further not helped by the out-dated version of Pandas running (0.19.2). It has a 4 year old version. I tried to do the assignments locally, but then coming onto Coursera to find the methods I've used aren't supported. This causes further frustation with the "go learn on your own" approach, as every resource you'll find will be using methods/functions from the latest versions. You then have to spend hours more finding legacy methods for what you're trying to do (which, in practice, will be useless as you will always be working on updated packages)
In my opinion, this course is not worth the money. I would highly recommend you trial its contents before deciding whether to pay for it or not.
By Amir M O•
Jun 10, 2019
Wish I could give it zero star.
1- The lectures are extremely poor (read the most helpful reviews and you see that a lot of people share this opinion).
2- Assignments are super difficult and not related to the lectures.
3- Assuming that you manage to solve the questions, now you have to deal with their defective auto grader which is royal pain.
4- They insist on using Jupyter (in my opinion a really messy environment). I used PyCharm which is the default IDE for python nowadays but their auto grader caused me so much headache.
Overall, this course requires significant changes and more respect towards the students who spend a lot of time on it. For me personally, it killed my motivation for pursuing Data Science and taking more courses from this instructor.
By Rahul R•
Feb 02, 2020
This course is very difficult. This is first of all not a introductory course. The instructor teaches basic stuff but the assignments were look like mountain. It is quite impossible for a beginner to solve this type of assignment problems without having a very good background in python programming and data structure handling.
I should recommend, the instructor should revise the course content. Please bring balance between what you are teaching and what you are expecting from student.
After taking this course, I personally demotivated from taking further courses in this specialization.
*********** I will recommend going for IBM data science specialization.********
By Marshall J V•
Feb 25, 2018
Would give this class a half star if I could. The material is covered way too fast and the assignments require knowledge of items not even mentioned in the class (let alone discussed). If you know the material well enough to get through this class, you don't need the class. The prof and TA refer to using Stack Overflow to figure it out early and often! Found this class to be a waste of time and money. I wanted to learn the material, but had to drop the class because I had no clue how to do the assignment after watching the lectures multiple times.
By Kyung H K•
Feb 25, 2018
I have no idea who rated this class five stars. The lectures do not prepare you for the assignments and the auto-grader will grade your answer as incorrect if you return a 17 dtype='float64' and they were expecting a 17 dtype='float'. Also, there's absolutely no feedback on your work except from the auto-grader, so there's no opportunity to go back and see a more elegant way of writing your code. I managed to get 90%+ for every assignment, but it was only because I spent over 10+ on the homework assignments for the last two weeks.
By Deleted A•
Nov 20, 2016
The jupyter notebook made this a horrid experience. Plus Coursera really doesn't want you to bother them with your silly questions, relying on peer-forums. If you scroll through the week's discussion forums, many student posts go ignored.
You can't drop the course past the second (I guess) week so the system will keep on keeping on long after you've given up on trying to figure out the janky notebook thing.
Will not return to Coursera for any reason. Breathtakingly bad experience.
By Thileepan P•
Apr 03, 2018
This is definitely not an introductory course. This is more of an intermediate level course. The teachers explain complex techniques in one or two sentences. The notebook demonstration in the video lectures are also very fast.
There is a huge gap between the contents in the lectures and the assignment questions. These points should be kept in mind while choosing this course. I think, I will not take other courses in this specialization.
By David S•
Dec 21, 2019
This course is poorly organized, the instructor doesn't clear the most important basic concepts and pitfalls, instead just gives a brief through what can be done. The assignments are terrible, cannot state the problem clearly, didn't say anything about text files issues which causes submission problems, waist a lot of time on it.
By Daniel D•
May 15, 2018
This was the WORST course I have ever taken on Coursera. The final exercise questions were not specific enough and the autograder SUCKED ASS. I couldn't even refer to a column in my dataframe after I closed the browser 3x and rebooted my machine and it still did not work. This course is a WASTE OF TIME. MOVE ON!!!