Chevron Left
返回到 Introduction to Data Science in Python

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
25,642 個評分
5,715 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....

熱門審閱

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

YY

2021年9月28日

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.

篩選依據:

5101 - Introduction to Data Science in Python 的 5125 個評論(共 5,665 個)

創建者 Souvik B

2020年6月8日

Not at all for beginnners. Fast-paced with more focus on self-learning and grinding,rather than focussing more upon the concepts. Dry presentation.

創建者 Konstantin K

2018年3月4日

Quite bad knowledge delivery from lectures. The course is rather self learning than course. A lot of vague points and uncertainties in assignments.

創建者 VARUN K

2017年3月4日

The course instructor could have been more elaborate with the examples. I felt there was a wide gap between the exercises and the course material.

創建者 Justin L

2016年12月6日

Assignments are challenging, but some questions are very vague and require lots of trial and error guesswork to get the autograder to accept them.

創建者 pouya S

2018年6月29日

Assignments are great to reinforce your learning. But the instructor does not cover many topics and leave you with a lot of questions unanswered.

創建者 Hanwen L

2019年8月15日

Please update the auto-grader such that is it compatible with current version of Jupyter notebook, very frustrating dealing compatibility issues

創建者 Hemanta B

2019年8月13日

This course is a nicely organized. However assignments are not completely clear. Especially assignment 4 needs more explanation and details.

創建者 Joel B

2019年8月1日

Subject matter was very good. Some of the assignments were not clear on instruction, and some of the Coursera functions were buggy or broken

創建者 Paul A

2018年11月5日

Material delivered a bit too rapidly to effectively assimilate. Often, further external research is needed to find solutions to assignments.

創建者 John W

2019年3月27日

I don't think this is a good enough course to "teach" you "data-science". All this does is give you an overview of things you need to know.

創建者 Ahmad A

2018年6月24日

The assignment descriptions needs to be precise (with psuedo code).And the statistics part needed a lot visualization to aid understanding.

創建者 Jordan K

2018年5月19日

The material is valuable and taught well. The lectures are impossibly fast paced (lots of pausing) and the assignments are often ambiguous.

創建者 Adam P

2022年3月13日

Assignments were more difficult than they needed to be because many of the directions were unclear. Otherwise, the class was interesting.

創建者 Vipin G

2017年12月16日

Great Assignments, Great learning, but requires good "prior" knowledge of Python and Pandas. This is more of a refresher course in Pandas.

創建者 Marat K

2017年11月11日

Much more time needs to be invested into theory of the data frames. The course is too lightweight for the heavyweight topic it's covering.

創建者 SHUVA M

2020年9月3日

Course materials should be scrutinized. It's like the mentor is going through a scripted page. I understood very little from this course.

創建者 Tobias T

2020年8月26日

Good course for the basics, but the assignments are very difficult as lectures do not cover everything which is asked in the assignments.

創建者 Greg S

2018年1月4日

Great Content. Course Auto-Grader was immensely frustrating. Videos aren't very helpful except to identify where to do your self study.

創建者 Sai S B

2020年6月19日

The course assignments are at a very good level. But, I feel the course doesn't prepare you for that. Most of the work is self-learning.

創建者 Kelsey S

2018年8月17日

The examples used are so small it's hard to understand how to use these skills in real-world situations if you aren't as used to Python.

創建者 Michal Z

2018年1月5日

There should be more Pandas API hints in lectures, it ware really hard to find optimal ways to perform operations on DataFrames I wanted

創建者 Francesco L

2017年3月5日

The course lessons could have been more specific and provide more explanations on many topics that are later required in the assignments

創建者 Jimi O

2019年5月28日

Lectures are interesting but coursework is challenging. It requires significant external reading and understanding to stand a chance.

創建者 BRUNO C D D F

2020年7月6日

The demanded exercises were way harder than the content taught. Also, the main teacher isn't didatic, he speaks in a monotonous way.

創建者 Morales J S

2020年6月21日

is good to make students to investigate but, in the whole course i was thinking that youtube teached me more than the course itself.