Ratings and Reviews for Introduction to Data Science in Python

Overall I would certainly recommend this course, I've found it immediately relevant in my field of science/engineering. It is fast-paced and difficult yes, especially for those of us with limited python experience, but that kick it gives leaves you with some solid, immediately-applicable skills. Where it goes well: Strong content and excellent delivery. Fosters independence. The course starts from the basics but accelerates at a fast pace, introducing you to roots of concepts but expecting you to expand on them yourself with outside resources rather than rote-learning. In this manner it leaves you VERY prepared to tackle unscripted challenges. Concise content. The lectures videos themselves contain almost zero fluff. The lecturer conveys relevant information in a very smooth and efficient manner. Replaying specific parts to revise or solidify understanding becomes a pleasure due to this. Where it could be improved: Could be a more polished. Time estimates for the assignments were WAY off. I do not mind a challenging assignment, however if it advertises that it will take 3 hours, I would hope not to expect to spend closer to 20 hours, however this certainly was the case. Multiply the estimated time by 4-5 to get a more realistic time. The assignment wording can sometimes be a little ambiguous. It's almost mandatory to go through the forum posts for clarification. I realise some things were noticed after the publication of the course, and contained by pinned posts in the forum, but perhaps if the next installment of the course could be updated, ironing out some of these wrinkles.

I found some assignment questions quite unclear. This, together with the grader sometimes marking answers as correct even though they were wrong, forced me to spend many hours trying to find the underlying problem to incorrectly answered questions down the line.

I appreciate why the data cleaning and debugging steps are included - I imagine this is a key component of working with real world data, but I think the time I spent debugging and cleaning could be better spent purely manipulating the data to get the answers to the questions in the assignments. I don't think the introductory videos on python are necessary - they would not be enough for someone to do the rest of the course. I would replace that with explanations on how to use jupyter notebook and getting more from the course in that way. In all i enjoyed this course, I particularly enjoyed Week 4's lectures on hypothesis testing.

Doesn't explain alot of important variation of the sintax, and says some wrong stuff as well. These two problems actually happen quite rarely, though. Pretty good course!

Amazing course! Well-thought out and just the right balance between instruction and self-learning.

I'm very happy with the course overall, especially the challenges that the graded assignments offer. The lecture covers just enough detail to give you a broad understanding of the topic, but allows room for self-discovery, as in having to read the docs to accomplish your assignments. I'm happy with the quality of instruction and level of knowledge that the lectures have as well. The main instructor was very articulate and demonstrated a deep knowledge and a lot of experience with Python pandas, as well as statistics. The discussion forums have been extremely helpful throughout completing assignments, and got me moving from where I was stuck. I've certainly leveled up my python and pandas (especially pandas) skills from taking this course.

I am a practicing engineer with over 15 years of experience.This course was definitely not for the faint of heart. While the lectures themselves were crisp and easy to follow, the homework assignments were truly a test of your patience and ability to think through the fundamentals. In all 4 weeks,I took way more than the predicted time to complete the assignments. I still gave the course a 5 because of what it taught me. I would never have learned so much had the assignments just been a rehash of the lecture examples. I applied the material to real world data analysis in my field with very good results. I could not have done the computations I did, if I had not taken the course seriously. There could be more clarity in the assignments especially in week 3 and week 4 but then that's the fun too - in real world data, there is no instructor to watch your back. So mistakes made during the course while frustrating for a working professional with limited time translate to better outcomes in actual work. I must also acknowledge Sophie Greene for her efforts to guide students to think through the problem statements.

Explanations of python were pretty coarse, the video was not helping much. I feel like I spent time doing 99% of python and 1% of data science.

Well, I was new to Python. And This course has great material and helps develop decent skills in working with Datafarmes, Series, and Pandas and Numpy libraries. Overall, I am happy with What I learned. But there are a couple IMPORTANT points to consider: 1. The assignments requires a huge amount of self-study and it takes way more than the suggested time to complete. 2. The assignment grader may act up or be very picky on data types and do not credit you for the right answer 3. The course can get very frustrating as the answer to the final question of assignment#4 determines whether you pass the course or not (it is 50% of the total grade!!). Although, you should be able to get to the right answer through the tips in the forum, it is really hard to figure out the solution on your own since there are many rooms for little mistakes which lead to the wrong answer. Suggestion: I think the questions should be designed in a way that there are small points for each step of the solution. So, We get to the solution step by step. Having 50% for just one final answer is not reasonable and makes it frustrating for the students. 4. The course subscription is monthly and it makes it even more frustrating when you are stuck with a wrong answer that holds up course completion. I think where huge effort is required to pass the course, having a monthly subscription rather than one-time payment for the course, is not a good incentive at all, but it is very frustrating when you get close to the deadline and can't fix your code to get the answer. Finally, I want to thank Dr. Brooks and staff (specially Sophie) for the good course. I would like to sign up for the next course in this specialization. But I am debating since I don't want to get stuck with the unreasonable monthly subscription method and frustrating assignment grading system. Thanks, Ershad

Very nice course! Given lots of confidence.