May 10, 2020
The course had helped in understanding the concepts of NumPy and pandas. The assignments were so helpful to apply these concepts which provide an in-depth understanding of the Numpy as well as pandans
Dec 10, 2017
Wow, this was amazing. Learned a lot (mostly thanks to stack overflow) but the course also opened my eyes to all the possibilities available out there and I feel like i'm only scratching the surface!
By Nikolay D•
Mar 24, 2019
It is disappointing that most of the course is basically self-learning from publicly available resources. If self-learning was what I wanted, I could do with reading the Pandas documentation instead and spare myself the subscription fee.
By Wei M•
Jan 25, 2019
This is a assignment-driven course, and the assignments are great. The course is not self-contained, and the assignment is much harder than the content of the course videos. It takes >8 hours per assignment, and it does require some previous programming experience.
I have seen complaints about the difficulty of the assignment. However, if someone really wants to learn how to do data science and programming, one cannot copy and paste everything from others' or some lecturer's code. Data wrangling is important work when dealing with real-life data, and he or she must knowing how to read through documents and extract information by themselves. There's no shortcut if you really want to learn Python and pandas. From dealing with real life data, I learned a lot in this course. However, I suggest that the lecturer should provide some simple lecture videos on how to read documents and how to effectively search for relevant content on the internet. Many students may not have appropriate programming skill background before taking this course.
Apr 15, 2018
I was really excited about the this course, and was really let down. This course is really, really poorly done. I would not waste time and money on this course when there are much better options out there. I feel like I've gotten little in return for my time and money.
First, there is no accompanying book (only slides). A self-contained accompanying book is a valuable resource, helping students prepare for lecture, and serving as a reference manual later on (I still regularly use my Coursera book on introductory Python). That there is no pdf reference for this class is indefensible (both of the other coursera courses I’ve had access to have had excellent self-contained books that followed the lecture). Instead, the student is directed to several other books they can purchase elsewhere.
Second, as several other students have noted, the timeframe for assignments is really unrealistic, taking much longer than projected (at least for me, and several other students). This is not acceptable when Coursera bills by the month. Coursera needs to provide a better assessment of the time commitments for the class. Moreover, several of the in-video quizzes are disconnected from the material, often requiring extra research. Consulting other resources is fine (it’s part of coding), but the point of the quizzes should be to give the student practice implementing a concept that was just introduced.
Third, the teaching is horrific. The professor is not engaging at all, but simply mechanically reads lines which often sound straight out of a user manual. The point of online videos is not to turn books into audio files- it’s to have a human talk/reason through problems with you. The teacher of the course should discuss the material, not recite a manual. A great example of well-done online teaching is Dr. Chuck Severance, whose videos the teachers of this course would do well to consult. In addition, the material is presented far too quickly.
Fourth, the title of this course is a misnomer: an introduction to data science would provide an overview of the tools, techniques and scope of the field. An extremely detailed introduction to Pandas, which is essentially what most of this course is, is useful if well executed (which it is not here), but it is not an introduction to data science.
A more minor complaint is the absolutely horrendous choice of the background. Showing different permutations of lifeless office drones is not exactly inspiring material for aspiring data scientists, even if this the reality of office life- it’s distracting at best, and at worst, deeply disparaging. Why not have just a plain colored background? Or anything else?
The experience of this class is making me question whether I will ever pay for a Coursera course again. The amount of time I’ve wasted on pointless exercises is not warranted by what I’ve learned from this class- in retrospect I would have learned more just by purchasing one of the books referred to in the class introduction.
By Jacob S•
Mar 10, 2020
I do not recommend this course. If in the end you do take this course don't waste your time with the lectures, 90% of the homework doesn't come from the lectures. In fact the first line in every homework assignment is:
"This assignment requires more individual learning than previous assignment"
This essentially translates into you using google to look up how to do the 90% of the homework they don't cover in the lectures.
Also this course should also be changed to be "Introduction to Data Cleaning in Python" because you do more data cleaning than anything else in this course.
I am sure this review will be buried behind all of the "top" reviews even though the most "helpful" reviews as voted by people in the course are all 1-stars.
I DO NOT RECOMMEND THIS COURSE.
By William G•
Jan 22, 2019
Important material, but taught in a far less optimal manner than Python for Everybody (or maybe Dr. Chuck's material is just the gold standard).
Material is explained at a high level extremely quickly, with very little explanation of the underlying fundamentals of what's going on. Videos are generally of the instructor talking, not actually slides depicting what happens when you're calling a function like loc.
Gold stars for the helpful forum posts from the TAs though - would have probably spent 2-3x the time if not for their posts. The week notebooks are also quite helpful - I recommend just reading the transcripts and following along the notebooks, and only using the video when something really does not make immediate sense.
By Shawn W•
May 09, 2019
Poorly designed course. Very little guidance or content provided, ended up getting most of my insights from stackoverflow...which I can do on my own.
By Nils W•
Mar 10, 2019
Wrost course I have participated in. The assignments aren´t solvable with the provided code. So one had to search and google for all snippets. That would be ok, if the assignment isn´t containing data cleaning every time. So you get an error if you won´t clean correctly and perhaps misses a whitespace. So a simple task gets complicated. And the worse thing is, some answers will displayed as correct but aren´t. So you won´t pass the next questions based on the previous questions.
You should know regex quite well and some other tool to be not so much frustrated. Be aware the assignments are way harder then it looks like.
By Ray M•
Jul 13, 2019
I cannot recommend anyone to do this course - it's ridiculously poorly constructed. I have done four other courses on Coursera (including several other python courses) and all were excellent. The quality of this course though is appalling in comparison.
FIRSTLY They do not TEACH any of the material. Instead they simply list - very briefly - a ton of functions/ methods/ objects etc without providing any real details of how they operate. Teaching the basics and then expecting the students to do further study and practice using those basics would be fine. Spending 30 seconds or less on a function / method/ objects is NOT teaching the basics. READING A TEXTBOOK on the topics covered was more effective then doing the course material!!! What kind of modern on-line course is less effective at teaching a topic than a textbook?
SECONDLY The autograder for the programming assignments is a joke. I took the course to learn how to code successfully. The autograder does not test that - it could not even get question 1 of assignment 3 correct. Instead, the students are expected to read through the forums and then spend hours making ridiculously stupid adjustments to corrects for errors present in the autograder. Seriously? If you are not capable of building a autograder that works, don't have programming assignments that require an autograder. But realistically, if you are not capable of building an autograder that works, you have no business offering an on-line programming course.
REALLY disappointed. This course should be removed until its quality is significantly improved - it detracts significantly from the Coursera brand name. If this was the first course I had done on Coursera, I would have thought the platform rubbish and would never have done a second course. Even now I am concerned about how many other of the courses are this unprofessional. I've gone from being a huge Coursera admirer and advocate to now not being sure how much I will use (or endorse) the platform going forwards.
By Divyasom M•
Nov 04, 2019
Personally I am rating this course at the lowest level possible.
Here are my reasons for doing so:
The course videos do not teach you much. The video lectures are super condensed and lot of information comes your way and actually trying that out on Jupyter notebook on the side easily takes 5-6 times. When you get down to the assignments, you will realize that videos only scratched the surface of the topic and in some cases some of the concepts to be used were not at all discussed in the videos.
You have to learn by yourself, and your best friends are StackOverflow, Google, Python and Pandas documentation. Once you have researched and spent hours putting together the solution to assignments, you will spend more hours struggling with the autograder (At this moment, I am stuck for over two weeks with the autograder at Week3 of the course). If you get the autograder to work then also all you are just going to get pass/ fail result and there is no actual reinforcement that the way you tackled a problem was an efficient way of doing so.
I would recommend this course only to someone who can spend 25-40 hours each week just studying for this course.
By Darien M•
Nov 14, 2019
This course is not conducive to learning, but rather to getting results. I understand that in the "real world" programmers would simply search the web for questions. This is because they need to produce results for their companies. We, as students, need to learn. We are not taking the course to learn what it is like to be a programmer, but rather to understand how the programs work and how to improve our thinking skills. This course taught me how to navigate Stack Overflow and other online resources for Pandas. I was pretty diligent about trying to understand what I was doing, but it definitely wasn't a requirement for the course. That is my problem: one could sneak by in this course without even understanding a thing. They could simply copy and paste code from the internet , tweak, hit submit and repeat until they have a 100%. Just a small example, in the last question we do not have to interpret our results in any way whatsoever, just get results. This is not learning.
The assignments are good and the TAs are helpful. They should be getting paid. The fact that we need so much help to complete the assignments should raise a red flag.
By Tan J X•
Jan 13, 2020
I found the lectures extremely dry and boring. The entire time I was watching the videos, I was just looking forward to the end. Meanwhile, the exercises were exceedingly difficult. I found myself using apply and groupby methods when they were only introduced in Week 2. Suffice to say, my first few hours on the course can only be describe as 'painful'.
I would suggest to anyone reading this to watch Brandon Rhodes' Pycon 2015 lecture. It was way more engaging, and his explanation of concepts were much clearer. The exercises were well paced, and after spending 6 hours or so on both the video and the exercises, my mind has never been clearer on Pandas. I urge anyone who has been recommended this course to drop it IMMEDIATELY. Putting your time into YouTube and Stack Overflow will definitely be more beneficial.
By Stefan H•
Sep 27, 2018
This is simply the worst teaching i have ever seen. the listed requirements are not what is required. instead I ended up googling the possible solutions for 3 hours until i gave up - since there is also no additional material to add. I don't agree with the professors expectations we will just magically know more than he taught in the course. I am paying to be taught at an acceptable level, and this surely was not acceptable.
disgraceful. He should not teach anyone anything.
By Colleen P•
Sep 18, 2018
This course was very frustrating. Sometimes the instructor was clear and other times, very confusing. The assignments were extremely difficult and included concepts that were never taught in the course. Suggesting we use Stack Overflow for help instead of simply teaching the concepts in the course was extremely frustrating. This is not an efficient way for most people to learn Python.
By Kevin M•
Apr 18, 2019
This course lacked written material to accompany the videos and the reference books are presented in a much different flow, so you are left to jump through books and posts to get through anything. Having the content packaged and delivered in succinct format is what I was looking for and this did not provide that.
By Sergei Z•
Sep 18, 2018
Absolutely terrible learning support. The professor does not supply helpful information what so ever for the assignments. He expects us to go out of our way to look up information on StackOverflow.com in order to solve the problems. His incompetence in actually demonstrating how this works is abhorrent.
By Michael O•
Mar 03, 2020
I'm not sure how this course got such high reviews when 90% of the time you'll need to go to Stackoverflow to find out how to do things. The concepts "taught" were so basic and barely touched the surface of the required knowledge needed to complete the difficult assignments.
By Davide C•
Feb 11, 2019
Lessons are not helpful if you start from 0 and want to learn. Had to search everything on my own. So what' s the purpose of them? Too little details and assignments too unclear.
I came here to learn not to show that I already know.
By Zhenxun Z•
Jan 12, 2017
I really like Prof. Brooks's way of teaching. He developed a very good introductory level course. Apart from some talks about data science in a whole, he concentrated on the preparatory work in this field -- data cleaning. Instead of delving into theories, he paid most of his attention to how to make things work by using python. I actually have a background in C, and I was a bit reluctant to learn python at first since C is already strong enough to attack most tasks. However, I have fallen in love with python now, and I think it is a much more suitable language for daily use especially when your projects aren't very large. Among its many merits, the best thing about python is of course its numerous libraries like numpy and pandas which free us from tedious low-level programming. I am quite convinced that I will move to python from now on.
In addition to lectures, I truly recommend you go over extra reading materials. Those articles are very thought provoking. For example, the first one "50 Years of Data Science" totally changed my previous view towards this field. It made me realize that data science is not a simple combination of statistics and machine learning, that it is a distinct way of obtaining new knowledge, and that its advancement shall benefit the whole science society.
About the assignments, those taught in the lecture are not enough and you should refer to python documents and stack overflow. I think knowing how to solve problems and where to find help is more important than solving problems itself, and that's why I consider those assignments well designed.
Finally, thanks to all the efforts made by the teaching staff.
By Shawn T R•
Jul 12, 2018
Overall a great course which really pushed me to improve my Python skills and get more comfortable with pandas, which is really powerful for data analysis work. It also showed me how awesome Jupyter notebooks is to use. I'll be using it in all of my Python courses moving forward, whether or not the course requires it. I will say though that the estimates for the amount of time the courses will take per week are way too low. This is a problem I've encountered on every MOOC platform I've ever used though. They really just want to get you in and saying that you'll be spending 15 hours per week on a course will scare many people away. I've easily spent more than that for some weeks in this course. In the end though, I didn't feel that my time was wasted. The assignments are challenging and really force you to get better at Python if you want to try to solve them on your own and not immediately resort to the forums. I'm probably just a bit of a masochist that way, and it honestly may have doubled the amount of time it took to finish the course, but I find trying to solve the problems with as little guidance as possible very rewarding. You just become a better coder overall.However! If time is a major concern and masochism isn't your thing I highly recommend just giving it a go for only an hour or so if you're stuck end then going to the Discussion Forums. There are very useful posts there from the teaching assistants that will show you the most efficient ways of solving the problems the "Pandorable" way and save you gobs of time. TL;DR = Loved the course and would highly recommend it :-)
By Nikhil K•
Jun 16, 2020
This course is not easy. You will have to spend a lot of time on the internet looking for answers. At times you may get frustrated, you may ask why i am taking this course if i have to look around so much for the answers by myself. But if you stick there, you will learn a lot. Maybe you will retain more because concepts were not spoon-fed to you but you found them. That journey is a huge learning experience.
I would not suggest absolute beginner to take this course. Learn some python , practice a bit and then join this course.
By Fabiano R B•
Jan 12, 2019
If you are looking for in-depth theory, you may be looking at the wrong place. The videos skim through some fundamentals, and sometimes give you some valuable hints.
But if you are looking for a challenging experience that emulates the real world, this course is definitely for you. The assignments will throw you to the wolves very early. You will have to research way beyond the videos to finish them in a elegant manner. It also encourages you to code in a "pandorable" way, which is a valuable skill.
By Jonathan J•
Apr 16, 2019
great course, but the auto grader needs updating
Apr 05, 2017
Dreadful course. Instructors saw no value in presenting elements of course that would help learners complete the assignments; rather you are sent off to teach yourself about uncovered techniques needed to complete the assignments. From some of the posts from previous students on GitHub, they resorted to deriving the answer from another means (Excel?) and simply providing the answer as a constant value, in order to receive credit for particular questions. Not exactly sterling knowledge transfer, from instructor to student! This course should be presented as a challenge course to people that have already learned Python Pandas from some other venue. (BTW, Pandas documentation is also dreadful, as of this writing.) This is definitely not the way to learn Python for Data Science if you are a busy professional software engineer. (Wish I had a good recommendation as an alternative.)
The only positive aspect of this course is the challenge to work with defined datasets, to complete specific tasks, during week 3. (This was as much time as I could afford to allocate to this course.)
From a 40+ year software engineer, with doctorate in CS, a part-time instructor at a private university, with a very challenging technology job in a multi-national corporation.
By Bart T C•
Aug 19, 2018
This course provides very little instruction. I really like learning by trial and error, and I think that is how coding is typically learned. Learning python from stack_exchange, however, is how I was already learning it, and I was doing fine. The whole problem of learning from stack exchange is that you don't know if you are doing things in the best possible way, which can be important for big datasets. There was no discussion of the best practices for complete an assignment, after it was turned in, and, in general, may functions were required to pass the course that were never discussed in the course. The entire weeks lecture could also be watched in about 30 minutes, which seems low to me. Most courses I have taken have at least three hours a week of lecture. I have friends who have taken this same course, and had a similar assessment.
By Carl G•
Apr 10, 2018
Not my style of course. Lectures is a mostly just a list of code snippets without any slides. Instead there is a background of 2 people just staring at their screens the whole time. Does not inspire one to enjoy Data Science as a field. Prefer a narrative explaining why and how with practical tips thrown in. Learning to code is more than just syntax. Good examples are the first chapter in Think Stats by Allen Downey and Andrew Ng's Machine Learning course. In this course the assignments took quite a bit of time to complete since lecture code snippets not very useful. Had to self-learn from web to complete assignments. Also took extra time by some trial and error to get right format of results. A more productive approach was assignments in A