Ratings and Reviews for Introduction to Data Science in Python

Pros: 1: The content of the course is really good. A lot of important staffs of Numpy and Pandas were given. 2: Even though the homeworks were a little bit difficult, I could practice what I learnt during the video through the homework. This helped me better memorize and grasp the knowledge. 3: The TAs in the forum were really nice and helpful. They tried their best to answer every question raised by the students. They even summarized the algrithoms to solve the homeworks and pointed out the bugs of the system. I definitely would like to give the TAs a star. Cons: 1, There are a few bugs in the autograder system. I had to adjust my right codes to go around the bugs of the autograder. This is a little bit ridiculous. I wrote right code with correct answer but I could not pass the autograder bucause the autograder had bugs! Obviously, these bugs had been raised by other learners for quite a long time. However, it seems the Prof.'s team didn't listen to the voice of the customers. They should improve the autograder to give the learners better experience because we paid to learn. 2 Some of the problems of the homeworks were not very clear. 3. The teaching style of the Professor is not my taste. I felt like he was just reading the content of a text book. A lot of new things popped up during the course without any explanation. The structure of this course was not well organized.

nice learning platform

Great course material! Learned a lot of useful information. My only suggestion to the instructors, would be to refine some small technicalities in the Auto Grader (such as Q8 for assignment #3, or Q5 in assignment #4), which sometimes prevent a correct answer from being awarded points. If you are considering taking this class, please be prepared to spend at least 50% more time than what Coursera estimates for each week's material!

This course is fairly difficult in regards to the assignments and the lectures cover a lot of material! But trust me when I say the that the lectures are sufficient to point you in the right direction for the assignments. For the most part I ended up using stack overflow when I was working on the assignments, this is nothing new since most of my past programming assignments consisted of me scrounging through stack overflow posts. This course did in fact teach me alot concerning regex and how to apply it on a pandas dataframe. I learned a lot when it comes to data cleaning and for that I think this course is well worth it! The material and how it's presented does add to the difficulty, but honestly it's a fun course if you sufficiently go over the lectures and use stack overflow for general aid.

+The assignments are quite challenging and test learning properly. (took me 12+hrs to finish assignments for week3/4) +The videos were informative. -A lot of very common functions, methods and constructs aren't given in the video and there is no supplementary reading material. You have to rely on other webistes/stackoverflow for a lot of your learning. -A few parts in the videos felt rushed, many useful constructs skipped in some topics. -Explanations of some fundamental concepts was missing. OVERALL IMPRESSION : Take this course if you are willing to do a lot of self-learning outside of the course and already have some degree of proficency with python.

I. (eg wasting 30mins on df.pivot() vs df.pivot_table()!)Think my next course will be more intermediate level in python.

This courser is one of the best course to learn data science according to me.

good experience

A bit hard but absolutely useful.

good