Ratings and Reviews for Introduction to Data Science in Python

+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

excellent

Too quick

Wonderful course to get started with Python's data manipulation and analysis libraries. The assignments in the course are really good to think and bring practice to improve your skills.

I think the pace of this course started out alright, but by Week 3, the assignment really turns it up to a new level. Similar for Week 4's assignment, even though there is barely any material covered in Week4. Almost seems like they rushed through half the course, essentially. It's nice that the Jupyter notebooks for the lectures are prepared with commentary, but it can get dull watching a lecture video which is essentially the instructor reading the notebook (and typing it out at the speaking pace). Unfortunately, while I learned a few things, I definitely still don't feel very well versed in the Python topics covered. Mostly I have lists of functions/methods in some libraries/classes to reference, with some idea of how to use them. But I would not feel confident working on a Python assignment yet, even if it was intended to only require Pandas, NumPy (and maybe a little RegEx).