Ratings and Reviews for Introduction to Data Science in Python

Not a bad course but would like to see more teaching of best practice solutions to some of the test and assignment questions. As most of the assignments require a lot of self-learning it would be nice to discover if our solutions are optimal or not. As it stands you can get a perfect score by writing for loops or other inefficient solution when there are quite possibly built-in pandas functions which could achieve the same thing more efficiently. Would like to learn more about pandas and best-practice techniques.

Overall a good learning experience. The assignments were challenging and time consuming at times which is primarily what I am basing my experience on. The lectures on the other hand fell short of substance and not so helpful understanding philosophy behind using prescribed python tools. Most of my learning was self taught trying to solve the assignments which I really enjoyed! The lectures felt rushed and crammed up. Instructor focused more on python tools for Data Science rather than why use Python for data science in first place and pros and/or cons it(tools) brings to Data Science. I felt I learnt more on why use python for Data Science from the course specialization "Python for Everybody" taught by Prof. Charles Severance from same University. The Jupyter notebook interface was great! I really like the fact that you could play with the code shown on lecture slides/videos. This course dwells deep into Python tools such as pandas. For python newbies (like myself) I recommend taking some introductory python course(s) which would greatly help with solving assignments on this course.

In general, the course is present in a coherent and concise way. This course mainly focus on pandas library in python. Finishing this course, you will have the essential tool to manipulate pandas series and dataframe. However, the course has room for improvement, especially the assignment section. Question 2 of week 3 assignment is ambiguous and the data set provided is prone to misleading. And I also think the data set provided for week 4 assignment is corrupted. When set the house price data's index to ['State', 'RegionName'], the multi index is not unique! Also, few of the university town names are not in the house price list! In a nutshell, if you are new to pandas, this is a good place to start.

The assignment is useful, however, the grading does not give much information on the submission except the points awarded.

Great course and very good lecturer. I recommend for every old and future Data Scientist.

I really like this approach of the specialization. Data wrangling with pandas is essential. Also referencing some controversial discussions reagarding the limits and problems we are facing as data scientists is appreciated. However one star less as as there is no feedback on the submissions. So I really don't know what was good and how can I improve my codings.

The Course assignments are challenging. Thank you

I really liked the course. I learned a lot.

An Awesome tutorial to start learning Data science using Python and its Libraries ( NUMPY, PANDAS and etc...)

The course is great for senior data analyst. However, you need to learn by yourself probability and statistics because they do not cover them in this course.