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Отзывы учащихся о курсе Introduction to Data Science in Python от партнера Мичиганский университет

Оценки: 13,609
Рецензии: 3,085

О курсе

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses. This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python....

Лучшие рецензии


Mar 16, 2018

overall the good introductory course of python for data science but i feel it should have covered the basics in more details .specially for the ones who do not have any prior programming background .


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!

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26–50 из 3,016 отзывов о курсе Introduction to Data Science in Python

автор: Henrik F

May 17, 2019

The difference between exercises and lectures is too big. You end up researching elsewhere more than just follow the course.

Exercises being graded is a challenge > installed grader version is different (older) than the note book. This led to the point that my exercises weren't graded due to exception because I used a more recent feature of Python Libraries

Week 4 programming assignment was a challenge: To pass the final question you need to figure out the previous questions as well, other wise you do not get the right answer. In case you got it wrong it is near impossible to figure out the root cause (because the grader doesn't give you elaborate clues where you might correct things). You do not get enough side information on your own so as to solve any issues on your own.

The content covered in the specialization would exactly be the things I'd want to learn, but the learning experience was full of bumps ...probably I won't follow up on the next courses of this specialization.

I heartily recommend an overhaul of this course, giving learners some more background by more explanation & providing more consistent information to master programming exercises.

On the positive side: Staff was helpful for a couple of open questions,. Even as the learning experience wasn't as good as anticipated I learned quite some Python stuff due to the contents of the course.

автор: Shawn W

May 09, 2019

Poorly designed course. Very little guidance or content provided, ended up getting most of my insights from stackoverflow...which I can do on my own.

автор: Jonathan J

Apr 16, 2019

great course, but the auto grader needs updating

автор: William G

Jan 22, 2019

Important material, but taught in a far less optimal manner than Python for Everybody (or maybe Dr. Chuck's material is just the gold standard).

Material is explained at a high level extremely quickly, with very little explanation of the underlying fundamentals of what's going on. Videos are generally of the instructor talking, not actually slides depicting what happens when you're calling a function like loc.

Gold stars for the helpful forum posts from the TAs though - would have probably spent 2-3x the time if not for their posts. The week notebooks are also quite helpful - I recommend just reading the transcripts and following along the notebooks, and only using the video when something really does not make immediate sense.

автор: SB

Apr 15, 2018

I was really excited about the this course, and was really let down. This course is really, really poorly done. I would not waste time and money on this course when there are much better options out there. I feel like I've gotten little in return for my time and money.

First, there is no accompanying book (only slides). A self-contained accompanying book is a valuable resource, helping students prepare for lecture, and serving as a reference manual later on (I still regularly use my Coursera book on introductory Python). That there is no pdf reference for this class is indefensible (both of the other coursera courses I’ve had access to have had excellent self-contained books that followed the lecture). Instead, the student is directed to several other books they can purchase elsewhere.

Second, as several other students have noted, the timeframe for assignments is really unrealistic, taking much longer than projected (at least for me, and several other students). This is not acceptable when Coursera bills by the month. Coursera needs to provide a better assessment of the time commitments for the class. Moreover, several of the in-video quizzes are disconnected from the material, often requiring extra research. Consulting other resources is fine (it’s part of coding), but the point of the quizzes should be to give the student practice implementing a concept that was just introduced.

Third, the teaching is horrific. The professor is not engaging at all, but simply mechanically reads lines which often sound straight out of a user manual. The point of online videos is not to turn books into audio files- it’s to have a human talk/reason through problems with you. The teacher of the course should discuss the material, not recite a manual. A great example of well-done online teaching is Dr. Chuck Severance, whose videos the teachers of this course would do well to consult. In addition, the material is presented far too quickly.

Fourth, the title of this course is a misnomer: an introduction to data science would provide an overview of the tools, techniques and scope of the field. An extremely detailed introduction to Pandas, which is essentially what most of this course is, is useful if well executed (which it is not here), but it is not an introduction to data science.

A more minor complaint is the absolutely horrendous choice of the background. Showing different permutations of lifeless office drones is not exactly inspiring material for aspiring data scientists, even if this the reality of office life- it’s distracting at best, and at worst, deeply disparaging. Why not have just a plain colored background? Or anything else?

The experience of this class is making me question whether I will ever pay for a Coursera course again. The amount of time I’ve wasted on pointless exercises is not warranted by what I’ve learned from this class- in retrospect I would have learned more just by purchasing one of the books referred to in the class introduction.

автор: Nils W

Mar 10, 2019

Wrost course I have participated in. The assignments aren´t solvable with the provided code. So one had to search and google for all snippets. That would be ok, if the assignment isn´t containing data cleaning every time. So you get an error if you won´t clean correctly and perhaps misses a whitespace. So a simple task gets complicated. And the worse thing is, some answers will displayed as correct but aren´t. So you won´t pass the next questions based on the previous questions.

You should know regex quite well and some other tool to be not so much frustrated. Be aware the assignments are way harder then it looks like.

автор: Stefan H

Sep 27, 2018

This is simply the worst teaching i have ever seen. the listed requirements are not what is required. instead I ended up googling the possible solutions for 3 hours until i gave up - since there is also no additional material to add. I don't agree with the professors expectations we will just magically know more than he taught in the course. I am paying to be taught at an acceptable level, and this surely was not acceptable.

disgraceful. He should not teach anyone anything.

автор: Colleen P

Sep 18, 2018

This course was very frustrating. Sometimes the instructor was clear and other times, very confusing. The assignments were extremely difficult and included concepts that were never taught in the course. Suggesting we use Stack Overflow for help instead of simply teaching the concepts in the course was extremely frustrating. This is not an efficient way for most people to learn Python.

автор: Kevin M

Apr 18, 2019

This course lacked written material to accompany the videos and the reference books are presented in a much different flow, so you are left to jump through books and posts to get through anything. Having the content packaged and delivered in succinct format is what I was looking for and this did not provide that.

автор: Sergei Z

Sep 18, 2018

Absolutely terrible learning support. The professor does not supply helpful information what so ever for the assignments. He expects us to go out of our way to look up information on in order to solve the problems. His incompetence in actually demonstrating how this works is abhorrent.

автор: Davide C

Feb 11, 2019

Lessons are not helpful if you start from 0 and want to learn. Had to search everything on my own. So what' s the purpose of them? Too little details and assignments too unclear.

I came here to learn not to show that I already know.

автор: Wei M

Jan 25, 2019

This is a assignment-driven course, and the assignments are great. The course is not self-contained, and the assignment is much harder than the content of the course videos. It takes >8 hours per assignment, and it does require some previous programming experience.

I have seen complaints about the difficulty of the assignment. However, if someone really wants to learn how to do data science and programming, one cannot copy and paste everything from others' or some lecturer's code. Data wrangling is important work when dealing with real-life data, and he or she must knowing how to read through documents and extract information by themselves. There's no shortcut if you really want to learn Python and pandas. From dealing with real life data, I learned a lot in this course. However, I suggest that the lecturer should provide some simple lecture videos on how to read documents and how to effectively search for relevant content on the internet. Many students may not have appropriate programming skill background before taking this course.

автор: Fabiano R B

Jan 12, 2019

If you are looking for in-depth theory, you may be looking at the wrong place. The videos skim through some fundamentals, and sometimes give you some valuable hints.

But if you are looking for a challenging experience that emulates the real world, this course is definitely for you. The assignments will throw you to the wolves very early. You will have to research way beyond the videos to finish them in a elegant manner. It also encourages you to code in a "pandorable" way, which is a valuable skill.

автор: Andrew

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.

автор: 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.

автор: 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.

автор: 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.

автор: 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

автор: 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.

автор: 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.

автор: 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.

автор: Florian M

Feb 03, 2019

I did this course as a 2nd year CS student with limited exposure to Python before the course. I had a basic understanding of syntax and knew basic structures like Dicts., Lists, Tuples. It took me 30h to fully complete the course - I did it in 2 weeks. I would recommend the book 'Python for Data Analysis 2nd' as supplementary literature. The course material is very very limited, which is by no means a bad thing. It just requires you to find answers by yourself. I really enjoyed it personally and would recommend this course for anyone who is interested in Data Science! Just make sure you know your Python basics beforehand.

автор: zqin

Mar 27, 2019

Honestly, I didn't want to rate the 5 star while I was learning the course, because the assignments of this course was challenging and the course videos didn't talk too much about the coursework. But after I finished the course, I found I have already learned almost all of the knowledge of the book "Python for Data Analysis" by Wes McKinney, which is also the recommended book in the course. And I can do data analysis work with python right now. You might think why do I have to register a course and then learn by myself, but what if this is a good chance to push you out of the comfort zone?

автор: Sourav S

Jun 04, 2019

The quality of the assignments is really good but the instructions for assignments is really poor.

I had to do read through the discussions to solve almost each and every problem. The assignments are really time consuming and challenging.

Also, I had to refer to stackoverflow for countless number of times to derive the logic.

The instructor has only touched upon the material but additional videos should be included by the TAs for the assignments.



автор: Jens L

Aug 12, 2018

Excellent learning materials. Clear concise explanations, but with the focus and majority of time devoted to activity-based learning: exploring the docs, practicing skills, and developing solution code. Even better is how subsequent lessons not only build on previous skills, they actually help guide and refine approaches even further. Well orchestrated progression of zone of proximal development. Thanks for a great learning experience!