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

4.5
estrellas
22,499 calificaciones
5,043 reseña

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 reseñas

PK

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

AU

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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76 - 100 de 4,966 revisiones para Introduction to Data Science in Python

por Roger v S

Oct 06, 2020

You will spend more time fighting the autograder than actually learning. You will learn more from youtube videos than this course. The only reason to do this course is for the certificate, even then, watch a youtube video or two before starting this course so that you can grasp the material. Also, before doing an assessment, watch the next weeks videos as the videos are a week lagged to the assignments.

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 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 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 Steven S

Aug 06, 2020

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.

por Zhengyi S

Feb 23, 2020

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.

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 Qin Z

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.

Thanks,

Sourav

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!

por Hamdy M E T

Mar 16, 2020

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!

por Carlos L

Oct 26, 2020

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.

por Sean C

Jul 29, 2019

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

por Pravesh G

Mar 02, 2020

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

por Ofir R

Jul 25, 2019

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 !

por Pavan A

Sep 28, 2020

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.

por Krishna M S

May 12, 2019

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

por Skywalker

Mar 10, 2020

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

por Sumit K B

Mar 05, 2019

Great course to bulild strong base on Pandas.

por John R

Aug 14, 2018

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.

por Stephen L

Jun 17, 2020

The course will teach you basics of the Pandas library, which is an essential skill. It also gets involved with some issues related to data cleaning, which is also essential, but felt a little like

There is very little peer-to-peer learning because there are no practice sets that peers can talk over, only assignments which Coursera's Honor Code naturally prohibits discussing. Hence, the learner never sees optimized code for solving real-world problems. I'm pretty sure I would have learned more if this course had provided more practice problems for learner discussions. For example, very inefficient iterations can be used to solved problems that should be solved in better ways with Pandas. I know that sometimes I was doing it right, but I think sometimes I wasn't and it would have been nice to see better code.