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學生對 密歇根大学 提供的 Introduction to Data Science in Python 的評價和反饋

4.5
23,722 個評分
5,325 條評論

課程概述

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....

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PK
2020年5月9日

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

AU
2017年12月9日

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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101 - Introduction to Data Science in Python 的 125 個評論(共 5,248 個)

創建者 Shreya B

2020年10月4日

The course lectures hardly covered what was asked in the assignment. For someone who has a full-time job scouting through discussion forums is extremely time consuming.

創建者 Girija S

2020年11月2日

Too much content condensed into 4 weeks of course. The videos are very fast with ~1.5 hrs every week and do not cover what is being asked in the assignments at all.

創建者 Patrick H M

2020年11月12日

Slamming down some notebooks is not teaching. Despite this shortcut does the lecturer still miss to show and explain the difficult cases of the different concepts.

創建者 Rachel B

2020年12月14日

not everyone who is proficient and knows their craft, is also good at conveying their knowledge...

in short- underwhelmed by didactic skills

創建者 rodania

2017年5月8日

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

創建者 amin s

2019年12月4日

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

創建者 Jeffrey D R

2018年5月7日

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.

創建者 Steven S

2020年8月6日

This is a hard course. It takes much more time than what is listed. It is frustrating because you need to do a lot of work on Stackoverflow or other sources to find solutions to assignments. The lectures aren't lectures, just quick talks about what can be done with Pandas, scipy and numpy. That being said, the professor treats you like a grown-up professional, gives hard real world problems with dirty real world data and asks for you to come up with questions to problems. That being said when you're done you look back and think, darn that was hard but I can actually apply data cleaning with python/pandas to data you might have lying around. As Poe said, It was the best of times and the worst of times, I couldn't decide if I loved the teaching style or hated it, but all in all I can say I learned a lot, though I complained a lot along the way.

創建者 Zhengyi S

2020年2月23日

The contents of the course are concise and it fulfilled basic requirements for fundamental data manipulation. Specifically, the exercises are excellent as they are real problems, which has many untidy problems to overcome during the process, and it's such a pragmatic train on me. Two suggestions: 1 is to add the answers of the assignments, because even though students pass the assignments, there might be better codes to refer and learn; 2 is to strengthen the problem description, as there're several negligence in those assignments. Overall speaking, the course helped me sort out the basic manipulation about numpy and pandas systematically.

創建者 Florian M

2019年2月3日

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.

創建者 Qin Z

2019年3月26日

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?

創建者 Sourav S

2019年6月4日

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.

Thanks,

Sourav

創建者 Jens L

2018年8月12日

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!

創建者 Hamdy M E T

2020年3月16日

Great Course and Awesome Instructor. The course is very practical and hands-on. All assignments starts with messy data and leave it up to you to start cleaning and manipulating the data with some modeling objective in mind which is what a real data scientist typically do. Thanks for the course , it was a really cool experience ! I really enjoyed the course and it was a bit challenging sometimes!

創建者 Oluwapelumi S

2020年8月5日

This course is really wonderful and tasking. You'll get to know the core foundations of Data Science and useful libraries Data Scientists use to manipulate data. The assignments are very thorough and deep. Many thanks also to all the teaching assistants who were available to help, especially to Sophie Greene and also to Yusuf Ertas. I look forward to completing the specialization!

創建者 Carlos L

2020年10月26日

Excellent course. I learned a lot about Phyton, even I thought I already knew what Phyton was, but here Phyton is used intensively.

The tests were really tough. I spent hours trying to figure out how to pass the tests. Also, there is a lot of help in the forums, and a lot of people willing to help.

創建者 Sean C

2019年7月29日

This course is excellent if you're looking to learn how to use Pandas inside Jupyter Notebooks. Assignments are autograded and feedback can be received immediately. Course is a few years old and discussion forums contain answers to common questions

創建者 Carla F

2020年6月18日

Um curso intenso e bastante prazeroso. Gostei de todas as etapas, os videos funcionam bem e estão construidos numa base introdutória, mas o desafio é pesquisar e pesquisar. Muito interessante mesmo!

創建者 Pravesh G

2020年3月2日

the course is designed very well. It covers data manipulation topics very well. It has excellent assignments which help in understanding the course concepts more better

創建者 Ofir R

2019年7月25日

Frankly, I did not watch the lessons at all, although they seem good.

The assignments were really great !

Challenging and very rewarding.

Really recommend the course !

創建者 Pavan A

2020年9月28日

Great course that teaches about how to process data in Python. The lectures are very code-based and the programming assignments help you learn new methods.

創建者 Krishna M S

2019年5月12日

Excellent course with assignments, But some elaborated videos on topics could help much better in solving the assignments in time.

創建者 Li Y

2020年3月10日

Very helpful and practical course, great intro to data science.

創建者 Sumit K B

2019年3月5日

Great course to bulild strong base on Pandas.

創建者 John R

2018年8月13日

It took me a while, but I finally figured out the problem with this class. The lectures provide some good information, but only rarely do they go into WHY a particular action/method/approach is used or WHY it will be important later. I had to do my own deep dives into available documentation to figure out how most of the functionality covered in lectures really works. This is not necessarily a flaw in the class, but it does mean the suggested time commitment for each week of class is significantly underestimated.

The assignments, while interesting, have the same issue as the lectures. Most of the time is spent using of Google to look up Pandas and Numpy functions or methods, or if we really get stuck, to see if someone on StackOverflow already addressed any questions you might have.

Put simply, the only different between this class and learning from a book is the class sets deadlines for the students to meet in the form of graded assignments.

Of course, the setting of deadlines is an excellent way to stimulate learning, and this is why I will continue on with the Data Science specialization.