Ratings and Reviews for Introduction to Data Science in Python

Awesome course to start study datascience using python, nice and hard projects to do!

Excellent course with very challenging assignments!

The main focus of the course is the introduction of the Pandas (series and data frames) library, which is very useful in data analysis. The last two assignments are quite challenging and time consuming, if you are not familiar with Pandas. Why the poor review: I'm sure that the intention of the teacher (Prof. Brooks) is for the student to be challenged and obtain familiarity with several "advanced" functionalities of Python. When I had finished the last assignment I felt that way, but not due to the lectures (only ~2.5 hours all in all). The pace of these lectures is too fast (probably because they are scripted). The teacher should slow down a bit and show some more examples (for inspiration watch Prof. Andrew Ng from Stanford lecture on machine learning). I'm not suggesting to show explicit solutions of the assignments, but just a few more examples such that the transition from lecture to problem solving is less "frustrating". Furthermore, the students are paying $79 for this course expecting thorough lectures on the topic. Reading the documentation of the Pandas library can be done for free...

This course was really useful. It progressed at a good pace and concepts were explained clearly.

it creates my base and provide me an overview of Data Science. Great assignments to play with real time data.

Good introduction to Pandas and Numpy. I enjoyed the assignments.

Great course! Covers important features of Python which are most likely to be used in Data Science. Programming assignments are really interesting.

tough but glad I make it through

Awesome work :)

The examples are a bit too extreme head on, I have experience with python but the level at which this is provided is quite hard for anyone to jump in and it should not be advertised as such