Ratings and Reviews for Introduction to Data Science in Python

Starts off well, then escalates way too quickly. Assignment 4 is incredibly complex and has poor guidance notes.

Is a great course, I don't give it 5 starts not because it is pretty tough (at least for me) but because the lectures are very simple compared to the HW. If you like to be challenged, I fully recommend this course

The course covers good grounds if you are new to pandas. However the content is pretty much a read-through of documentation and assignments are designed poorly: 1) There are loads of knowledge required to finish the assignment that are not addressed in the course. You will need to find those out yourself online, which in itself isn't a problem but you are also paying coursera for the time when you pretty much do self-learning 2) Due to how assignments are graded, you have to provide EXACT answers as the instructors wanted to see, meanwhile you don't get all information needed on what should be the right answer as certain parameters of the assignment are not clearly defined. The forum is disorganised and you end up spending a lot of time browsing through historical posts, some of which remain unanswered after months 3) Too much time spent on data cleaning. Granted that in real world projects data cleaning is at least 80% of the time but this is a learning course. You don't get to spend a lot of time to practice contents covered in video but struggling with the random complexities introduced by the raw data + specific results being expected. This leads to a frustrating experience. Suggestion to the course instructor: re-design the assignments to make sure students spend more time on key points covered by video. Have one assignment focused on data cleaning, but not all of them. Also review forum questions and understand where people get frustrated, and improve your instructions in the assignments. Suggestion to fellow students: it is probably best to enroll the course, note the content/ resources, quit (so you don't need to pay) then learn yourself on google/ stackoverflow. This will be pretty much the same experience.

There are several inherent problems with this course and how it is structured. I would like to preface this review by stating that I am likely below the level of python mastery required to complete the course; I came in with a simple background of some time spent learning from introductory texts, but I've never worked with the language professionally and I have been out of practice for a couple years. The course is labeled 'intermediate', though how 'intermediate' is unclear since there is only one elementary course recommended to get you "up to speed" enough to take the class. I used my free week as a test to see if my background was enough to be able to hang with this; it was not. However, even for someone with more depth of understanding than me, this course is poorly designed to teach. Each lecture is between 2 and 10 minutes long, and they do a very poor job of explaining concepts. The notes provided in the supplied notebooks lack any sort of meaningful documentation, and so it becomes trivial to get lost as the lectures go on at lightning speed and you have no comments or notations at all in-text to explain how one thing they did is different from the next. Furthermore, the difficulty and complexity of concepts spikes up rapidly. Using the in-lecture questions as a barometer, the complexity jump is like going from addition to calculus in the blink of an eye. The first in-lecture question during one of the early videos requests you make a very simple change to a supplied piece of code to add three numbers instead of two. Two in-lecture questions later you're asked to create a list of all possible combinations of a number and letter system for a hypothetical internet company based loosely on concepts you learned 15 minutes ago and never before had a chance to break down or practice in any real detail. After quiz 1 is where I threw in the towel. Looking at the future assignments, as well as the discussion board, things seemed like they would only get worse, not better. Assignments are highly complex and rely on an understanding of python well beyond what this course, and the one before it, will give you. Users with years of programming experience were having to rely on google, text books, and stack exchange to solve the assignments. This course is too light on details and too focused on speed. You'll essentially be teaching yourself what you're supposed to do. As my first attempt going through a MOOC, this was a letdown. Part of this is on me, as I do not have the requisite background to fully engage and succeed here. Part of it is on the structure of the course, which truthfully seems to focus on speed and ease for the creators rather than in depth of understanding for the students. If you're considering this track, I recommend instead picking up some textbooks and going through this yourself. You'll lose the certifiable, but you'll have a less frustrating time.

some of the automatic revision has some issues.

great!!! learned a lot!

Very good course for using python for Data Science

Thank you Coursera for providing such a wonderful course.

The videos are pithy and the exercises are challenging for beginners. This class is an introductory course, but not from scratch. If you haven't dabbled with Pandas before you may find this class extremely fast paced.

This course zeroes in on the best prerequisites to start towards data handling with python.