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Opiniones y comentarios de aprendices correspondientes a Introduction to Data Science in Python por parte de Universidad de Míchigan

14,427 calificaciones
3,278 revisiones

Acerca del Curso

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....

Principales revisiones


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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51 - 75 de 3,207 revisiones para Introduction to Data Science in Python

por 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.

por Mahmoud A F A

Mar 04, 2020

the course speed is very highand assuming high level of knoweldg

por Ray M

Jul 13, 2019

I cannot recommend anyone to do this course - it's ridiculously poorly constructed. I have done four other courses on Coursera (including several other python courses) and all were excellent. The quality of this course though is appalling in comparison.

FIRSTLY They do not TEACH any of the material. Instead they simply list - very briefly - a ton of functions/ methods/ objects etc without providing any real details of how they operate. Teaching the basics and then expecting the students to do further study and practice using those basics would be fine. Spending 30 seconds or less on a function / method/ objects is NOT teaching the basics. READING A TEXTBOOK on the topics covered was more effective then doing the course material!!! What kind of modern on-line course is less effective at teaching a topic than a textbook?

SECONDLY The autograder for the programming assignments is a joke. I took the course to learn how to code successfully. The autograder does not test that - it could not even get question 1 of assignment 3 correct. Instead, the students are expected to read through the forums and then spend hours making ridiculously stupid adjustments to corrects for errors present in the autograder. Seriously? If you are not capable of building a autograder that works, don't have programming assignments that require an autograder. But realistically, if you are not capable of building an autograder that works, you have no business offering an on-line programming course.

REALLY disappointed. This course should be removed until its quality is significantly improved - it detracts significantly from the Coursera brand name. If this was the first course I had done on Coursera, I would have thought the platform rubbish and would never have done a second course. Even now I am concerned about how many other of the courses are this unprofessional. I've gone from being a huge Coursera admirer and advocate to now not being sure how much I will use (or endorse) the platform going forwards.

por 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.

por 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.

por 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.********

por 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.

por 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.

por 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.

por 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.

por 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.

por 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!!!

por Saulet Y

Dec 13, 2019

Very disappointed! The assignments are unclear. To complete the assignments, you need to google on each question especially in Week 2 and 3. If you go to "Forum" page, you could see that there are more than 1400 threads in Week 2,3, which means a lot of students ask questions. The course is really really bad!

por 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.

por rodania

May 08, 2017

One of the worst course I ever take in coursera. The instructor just writes codes on front of us without explanation.

por Amin s

Dec 04, 2019

terrible course please improve teaching efficiency and give a proper realistic assignments

por Tural H

Mar 05, 2020

Very fast pace, no clarity of the scope and poor leacturing

por RobertD

Mar 06, 2020

The autograder wars made this a bad experience

por Jeffrey D R

May 07, 2018

Like many others, I give this course a high rating while lodging a minor complaint that there wasn't much instruction provided. The lectures were excellent, if brief; it's hard to imagine anyone having objections to the instructor. But in terms of teaching the material, it was a bit of a drive-by. The lectures show a few examples, while not explaining the syntax or the various parameters. You have to draw that out of web sites and cheat sheets. If you're not adept at doing that, proceed with caution here. In the end, I was worn out from the effort, but felt that I had gained a lot.

The assignments were challenging for me because this was my first hands-on experience with Python, much less with Pandas. I did not find Stack Overflow as helpful as the instructor suggested. Nor did I find much help in the forums, but that's not quite my style.

My bottom line is that the course was time well-spent, but it could easily have been a six-week course with a more deliberate pace through the various pandas mechanisms such as merging and grouping.

FWIW: My recommendation is to get to know Jupyter Notebook early and follow along with the lectures by opening the Week[x] files in the course download folder. You can pause the lecture while you go play with the code to make sure you understand it. Also, I recommend working with a local version of Jupyter and keep your files local. Otherwise, Jupyter loses connection to the kernel, and stops being able to save your work. The messages are disconcerting, and if you've worked yourself into a frenzy, they can cause panic and confusion. So do all the work on your machine and then upload the whole assignment when you are finished. You upload on the "Create a Submission" screen; it takes only a sec. You won't even have to worry about details like file paths; they'll be the same either way. Once you get the hang of Jupyter, you can settle into a work routine. Learn some of the keyboard shortcuts.

por Zhenxun Z

Jan 12, 2017

I really like Prof. Brooks's way of teaching. He developed a very good introductory level course. Apart from some talks about data science in a whole, he concentrated on the preparatory work in this field -- data cleaning. Instead of delving into theories, he paid most of his attention to how to make things work by using python. I actually have a background in C, and I was a bit reluctant to learn python at first since C is already strong enough to attack most tasks. However, I have fallen in love with python now, and I think it is a much more suitable language for daily use especially when your projects aren't very large. Among its many merits, the best thing about python is of course its numerous libraries like numpy and pandas which free us from tedious low-level programming. I am quite convinced that I will move to python from now on.

In addition to lectures, I truly recommend you go over extra reading materials. Those articles are very thought provoking. For example, the first one "50 Years of Data Science" totally changed my previous view towards this field. It made me realize that data science is not a simple combination of statistics and machine learning, that it is a distinct way of obtaining new knowledge, and that its advancement shall benefit the whole science society.

About the assignments, those taught in the lecture are not enough and you should refer to python documents and stack overflow. I think knowing how to solve problems and where to find help is more important than solving problems itself, and that's why I consider those assignments well designed.

Finally, thanks to all the efforts made by the teaching staff.

por Shawn T R

Jul 12, 2018

Overall a great course which really pushed me to improve my Python skills and get more comfortable with pandas, which is really powerful for data analysis work. It also showed me how awesome Jupyter notebooks is to use. I'll be using it in all of my Python courses moving forward, whether or not the course requires it. I will say though that the estimates for the amount of time the courses will take per week are way too low. This is a problem I've encountered on every MOOC platform I've ever used though. They really just want to get you in and saying that you'll be spending 15 hours per week on a course will scare many people away. I've easily spent more than that for some weeks in this course. In the end though, I didn't feel that my time was wasted. The assignments are challenging and really force you to get better at Python if you want to try to solve them on your own and not immediately resort to the forums. I'm probably just a bit of a masochist that way, and it honestly may have doubled the amount of time it took to finish the course, but I find trying to solve the problems with as little guidance as possible very rewarding. You just become a better coder overall.However! If time is a major concern and masochism isn't your thing I highly recommend just giving it a go for only an hour or so if you're stuck end then going to the Discussion Forums. There are very useful posts there from the teaching assistants that will show you the most efficient ways of solving the problems the "Pandorable" way and save you gobs of time. TL;DR = Loved the course and would highly recommend it :-)

por 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.

por 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?

por 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.



por 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!