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学生对 密歇根大学 提供的 Introduction to Data Science in Python 的评价和反馈

4.5
26,489 个评分

课程概述

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....

热门审阅

YY

Sep 28, 2021

This is the practical course.There is some concepts and assignments like: pandas, data-frame, merge and time. The asg 3 and asg4 are difficult but I think that it's very useful and improve my ability.

PK

May 9, 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

筛选依据:

126 - Introduction to Data Science in Python 的 150 个评论(共 5,806 个)

创建者 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!

创建者 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!

创建者 Oluwapelumi S

Aug 5, 2020

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!

创建者 YIJUN F

Mar 8, 2021

Overall the course is great for people who want to begin with data science. The skills it incorporate are very useful. The only thing to improve is that we could be given more hints when doing assignments. Sometimes we are not familiar with what can be done with Pandas, so it took a lot of googling to complete the assignment.

创建者 Donald W

May 26, 2022

Excellent course, even if you have taken other Python courses or if you use Python regularly. This course provided a good introduction to many ways you will use Python in real-world applications. The assignments were challenging enough and some required research on your own, which is exactly what you do with real problems.

创建者 Robert G

Jun 2, 2022

Very interesting and hands-on course. Especially with the assignments not being timed and instead being allowed to google, but the assignments still being appropriately hard. The assignments promote problem-solving on the fly and finding the help you need on stackoverflow, google, etc.

创建者 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

创建者 Francis J A

Oct 24, 2020

Great introduction to applied data science. The weekly assignments are challenging and varied, and students are required some independent studying outside of the lessons. The forums are also quite helpful in approaching the assignments.

创建者 Swapnil S

Jul 12, 2022

Really impressed by the material and quality of instructions to teach this complex topic. I felt the assignments were appropriately challenging to apply concepts taught in the lecture. Well done and thank you!

创建者 Carla F

Jun 18, 2020

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!

创建者 Pravesh G

Mar 2, 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

创建者 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 !

创建者 Mengru Z

Mar 15, 2021

Very interesting course to guide you through from the basics of pandas. Teaching staff is of great help throughout the learning process, with speedy replies.

创建者 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.

创建者 Krishna M

May 12, 2019

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

创建者 aborucu

Apr 20, 2021

Prof Brooks, Yusuf and Jimi have worked out engaging but also demanding applied course on the subject. Thank you very much

创建者 Teck F

Feb 24, 2021

Discussion forums are very useful. Exam questions are challenging for beginners but doable. Good teaching.

创建者 J D

Jul 15, 2022

Great course, but expect to really work. The assignments force you to get a good grasp of the material.

创建者 Daniel F L V

Mar 5, 2021

Excellent course! The professor is super clear and the content was really well organized!

创建者 Li Y

Mar 10, 2020

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

创建者 Hảo T K

Nov 5, 2020

This is the only course worth in the specialization

创建者 Sumit K B

Mar 5, 2019

Great course to bulild strong base on Pandas.

创建者 Mohammad T N

Sep 21, 2020

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创建者 John R

Aug 13, 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.

创建者 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.