Ratings and Reviews for Introduction to Data Science in Python

Very well prepared course, good quality video and audio too (some of the older courses have crappy audio)... this class gives you enough information to allow you to research and attack new problems on your own

Great course for data preparation for ML which is sometimes neglected in other courses. Great instructor. Useful assignments. Assignments require research on your own which is good. I would recommend to maybe make the course longer and cover more topics (in-depth string processing etc.), because it felt a bit short. Thanks Dr. Brooks for putting this together.

Excellent course. Good classes and the assignment push you to go further!

A lot of knowledge, sometimes too dense. Treats you like an adult and encourages you to look on your own. Very useful.

good solid intro to python munging.

This course was a good introduction to using Python for data science. I found the coverage of Pandas to be especially beneficial.

Great course, it would be nice to have more interaction and feedback from TA's.

This is a great course with excellent materials and very practical assignments. The course forum is more than supportive, I won't be able to complete this without helps from my peers and all the teaching staff.

The course is quite demanding from the get go. If you are trying to get by with casual interest, then this is not the course for you. Much of my December vacation (which I had earmarked for playing video games) was spent coding on this course. The biggest gripe I have about the course is the grader system. It gives a binary output indicating whether you got the question right or wrong. Unfortunately, often that is not good enough, to debug your code. I spent hours figuring out what's going on. The forums were also not helpful, since there were not many taking the course. At the end of all this, if I ask myself, did I learn a lot? The answer is probably no. However, I did get a lot of coding experience. Debugging experience. We have many databases (MySQL, MongoDB, Cassandra, etc), which have far more powerful features than what pandas can do. Therefore, as a system designer, it is unclear to me as to why I would ever pick Pandas over the rest. It appears quite slow (compared to the likes of time tested databases). It offers very few features (when compared to a DB). Lastly, I can use it only with Python. To me, it appears to be a no-brainer to use any one of those DBs to store, modify and massage my data. Maybe there are valid applications that can make use of Pandas like features, but I did not learn that from the course Summary: Better Motivation to use Pandas over standard Databases Better grader design.

To be an introductory course I struggled a lot, is a very practical course, and the assignements encourage you to learn more. This is the best technical course I have taken. Lo recomiendo ampliamente