Ratings and Reviews for Introduction to Data Science in Python

In the begining, there were practice questions at the end of each video. As I progressed, I obseved that only assignments are there. I would request you to provide more questions so that we could better insights and get more hands-on experience. It will help us to build strong problem-solving skills. Thank You.

Very poorly done course, with no real structure and lack of real world applications. Just a bunch of material picked up from the book with a dry format resulting in very slow learning outcomes. I believe the course from UPenn is superior to this one. Do not recommend!

I loved the course. It is necessary to have a base on python, but I fininished learning a lot, more than I ever though I would.

In order to get used to the best coding practices, can you send me the corrected versions of the 4 assignements of this course please ? Fabien

good

The lectures are good. The quizzes are silly, because they test mostly esoteric knowledge that I would look up when I need it rather than the basic understanding needed to do real data science work, data cleaning in particular. The projects are also unnecessarily complicated to the point that someone from the course has to post examples for almost all questions. If we are going to receive that kind of general help, why not just make the explanations better? In the real world, I would simply ask the project stakeholders questions when something is ambiguous. Requirements gathering is not an objective of this course though and simply looking in the forums for explanations does nothing to advance that goal even if it was within the scope of this class. The goal of this course should be to give the student an understanding of the tools involved, not do a lot of gymnastics to understand vague instructions and then apply oddly specific pandas functionality. I say all of this as someone who has been doing data cleaning with python/pandas for several years and was looking to just formalize things I have learned as needed. I will probably not bother to complete the course, because the final assignment and quiz have no real learning value and a Coursera completion certificate is of little value.

1. Recommend immediate termination and removal of this course due to the disservice to the field. The course is so horrible it convinces students that data science is not for them. 2. It appears that Brooks has only superficial understanding the material himself, as he is unable to explain it. 3. Lectures are waste of time, consisting of watching Brooks speaking as someone types what he says into the files already downloaded. 4. No relationship between lectures and homework assignments. 5. Repeated references to promote Brooks’s book. Lectures are so useless, his book likely only suitable for lining birdcages. 6. Repeated acknowledgment of inadequacy of lecture material with Stack Overflow cited as primary resource for learning. 7. Homework assignments a. Incredibly poorly written, as if student inability to complete them is the principal objective. b. Auto-grader errors incomprehensible and fail to indicate which part of the assignment has issue. c. Auto-grader reports errors that are actually auto-grader processing problems. TA in discussion forums attempts to interpret, without success. 8. Discussion forums a. TA complaints not enough time to support students b. TA agreement assignments poorly written i. Attempt to balance helping students without disclosing actual solution, with infrequent success ii. Repeated apologies and responds there are notes on where to improve (dated over a year ago, no changes made) 9. I have been programming since yellow paper tape. I know a terrible course in my field when I see one. With so many negative reviews, why are the problems in this course not addressed?

The assignments are a bit difficult especially assignment 1 with a lot of regex

Files are not imported. Assignments are challenging. Start with an intro course first.

sometiemes the questions are not detailed enought!