I have loved using Coursera to learn Python and have really enjoyed the Python University of Michigan courses I've taken so far. Unfortunately, this is not one of those courses. There is no accompanying textbook or reading, only videos and then practice code. The instructors in the videos don't provide any explanation of the syntax, and simply tell you what the code says which you can already clearly see. Basically they read the course syllabus and the lines of code to you and provide no explanation, i.e. "today we're talking about lambdas, here is code where we're using that." You may as well google articles about each topic in this course and you will probably gain more understanding of these concepts.

This was by far the worst experiance I had on coursera. Assignments were way too hard. Had to go online and do research all the time. Of course it is good to do online research time to time but I felt frusturated cause I couldn't do anything without a research. I felt like lecture videos couldn't explain the topic properly. Didn't find readings usefull as there are too little (2-3 useless non introductory readings only) (- -_ - -) would expect from an introductory course to have HANDY cheat sheats. And also I thing we should have been given easy examples followed by harder ones. I have taken 6-7 courses on this platform and haven't been frusturated more before. Below my expectations, way below

I have a decent knowledge of python, this course tries, initially to introduce Pandas. In my opinion, the way they try to do is bad. The material is not available, so, no way to reproduce on the student side the examples. During the course, there are also some small checkpoints to see if the example were clear enough. Honestly, without data sets, without proposing (many) exercises, it seems all useless. They expect that the students get everything immediately (they claim that you don't need to know the lambda function, but expect you to get in in 2 minutes of a lesson). I discontinued this. I will check for other materials, books, and more to deepen my data science knowledge in python.

This course was extremely bad. Reading a video where someone simply types at you and monotonously reads exactly what they type is excruciating. The text moves too fast to absorb anything remotely complex, the presenter has no personality whatsoever, and the course mostly amounts to a guided tour through StackOverflow. The autograder fails to compile code that works but isn't efficient, and many quiz questions are worded too ambiguously. Then when you get questions wrong due to bad wording, you can't immediately retake the quiz! I've taken several Python MOOCs, and this was not only the worst by a mile... it was the only bad one. I refuse to waste any more of my time on this.

Existe uma falta de teoria, o conteúdo é quase integralmente apresentado por meio de exemplos em tempo real com o professor que da a falsa impressão de ser fácil.

As tarefas da semana 3 e 4 são bem difíceis, dependem muito de você correr atrás do conteúdo e documentação dos comando porque o professor não apresenta alguns (e são esses alguns que vão travar seu progresso por horas e horas). Além de difíceis consomem bastante tempo, o curso diz que o tempo aproximado de conclusão dessas tarefas são de 3 horas, eu demorei pelo menos 12 horas em cada. Para piorar o auto corretor utiliza testes secretos então você provavelmente não saberá qual a origem dos seus erros.

This course is a really bad introduction to Data Science. You do not learn how to code for Data Science, they just give you a list of functions without really teaching you how to use them. Then in the tests you get tested on a lot of things that were not explained and you end up searching how to do most stuff on Stack Overflow.

I came here to learn stuff in an organised way, not to learn function after function. The things tested in the exams should be about what you teach, and not whatever you want. This course asumes you have a background in Python and also a background in using it for Data Science, which basically means it is not an introductory course.

i will give 0 star if i could. first of all, the course itself like a lot of other reviews said, leaking of learning and class material. secondly, the assignment and the course lectruing are like two seperate phases, the course lecturing are super simple while the assignments is super hard. Thirdly, you should be careful with the subscription, i only go for the 'introduction to data science in python' this course only, it has it is own page and enterance. And the course should be opt out once you have finished the course, but it is not. it will tell you that this course is some what one of five course,so the subscription continue, it is so tricky.

I wouldn't recommend this course to people who only read the material and answer the exercises, I wouldn't recommend this course at all!!, Run and don't look back, if you want to learn pandas libray (that is the focus of this course) better go to other courses because the material lacks the deepness necessary to pass the course. If you like to learn purely by yourself and read past threads from forums to resolve your doubts then this course can expand your knowledge of the pandas library and managment of data in the python language but at cost of your time, pain and sweat of trying to understand in the first place why you took this course.

Nothing like an introduction to anything. The langauge and videos are away talking in a language only established programmers would understand within only a couple of videos. I followed the recomendation to do an "intro to Python" before starting this course - but the knowledge gap between the two is way too wide. Given programming is a practical exercise there is way too much talking - most of it using computing terms I don't understand. I'm stopping work on this as I'm just having to go round and round re-listening to the videos to try and make sense of it. Could just be me, but i don't think so.

Very disappointed and honestly shocked that this course has the rating it does.

I enrolled in this course expecting to be taught. Instead, I have to pause lectures every few seconds to find a free YouTube tutorial or Stack Overflow article that actually explains the content that the instructor mentioned (because he never goes to a level of detail necessary for what can be reasonably considered "teaching").

All this leaves me wondering: Why am I paying for this?

I cancelled my subscription to the Specialization after taking a look at Assignment 3 and have no intention to finish the course.

Really hard to follow the course, and the instructor was not really explanatory to students, he seemed like he was just talking to himself in the mirror and everyone else should have his knowledge

Assignments and quizzes were not really easy to follow, too many questions for 1 specific assignment with fewer instructions

I did not like the course or the instructor at all. they definitely rearrange the course and its material to suit its title "Introduction"

Week 4 started all of sudden with p-values without some basic explanation of it really is in statistics and data science.

This was my second course with Prof. Brooks as the instructor. I gotta say, both were awful. He expects us to find info on what we are trying to learn, on our own. The assignments are completely different from what we are taught in the videos, which is well, minimal.

Pathetic. We have to find new functions on our own to complete the assignments. If I wanted to research all about Pandas library on my own, I wouldn't have taken up this course in the first place! Even in the lecture videos, the professor doesn't even bother to explain the functions properly.

I really wanted to like this class and was looking forward to learning data science in Python but this isn't the way to do it. The instructor glosses over material without explaining it and the assignments require a large amount of research and outside learning to complete. If I have to learn how to do the assignments from Google and Stack Overflow, why am paying for this course? I've taken other classes on Coursera and am pretty good with Python and self-learning but this is pretty terrible. Overall I expected better out of University of Michigan.

I found there were a lot of problems with the systems supporting the learning and assessments, namely the implementation of the Jupyter Notebook, which kept on misbehaving (it wouldn't save your work, and then it would stop giving outputs for your code). I ended up wasting a lot of time trying but failing to resolve these technical hitches, and time is the most precious resource for any student / programmer, and so I unenrolled from the course. I am now going to find an alternative sequence of courses to learn about data science along with Python.

This course is good but instructor is very bad..... Not providing good course lectures and materials... The lecture is very fast and not covering all the things being asked in the assignment... I am leaving this course due to this.. I have successfully done other python courses, because there, the instructor was very good and his teaching style was awesome...

I have wasted lot of my times enrolling in this particular course... Though the course conception is good, instructor and course materials are not up to the mark....

the instruction is very poor: when one decides to learn online, it´s expected that it will have the content related to the subject, and this course does not. The content is just showed, very fast, no details, and there are several tasks to accomplish, the level of them is much higher than what you have gotten in the videos and lectures, so, one will have to do a lot of extra research and learning outside this platform. if the person wants the certificate, ok, but the knowledge will come actually from other sources.

Too much research left for the participant. As one of them, I found no difference between going to Stack Overflow or the official documentation websites to figure out myself how some packages worked, as this was basically the same instruction provided by the instructors. I have decided not to continue further training given by University of Michigan, as there were other specialization that made a far better work increasing the course difficulty. Highly recommended to tag this course as of "Advanced" (difficulty).

While i can appreciate the value in getting resourceful at finding information online, this course was essentially 99% google and stack overflow with 1% referencing materials learned in the course. I spent many hours googling exhaustively for answers and reading through the forum where there were numerous bugs noted by the staff contributors. The information required for the assignments could and should have been presented better to achieve the same effect without the hours of independent research.

mal explicado, el profesor no explica los temas, solo los enuncia y tienes que buscar todo el material fuera de la plataforma, lo cual ocasiona que sea un curso muy complicado y que te tome muchísimo mas tiempo del que debería. Yo no siento que sea un curso, lo veo mas como una oportunidad para certificar si ya conoces todos los temas. Como consejo para los que quieren hacerlo, solamente lean las libretas y busquen los temas por internet, el profesor no les servirá de nada. dejo 1 estrella ( MUY MALO)

Lectures are descriptive but do not explain. Very few practice exercises. Assignments do not reinforce lectures but require you to learn and implement new things on your own. You will finish each week having practiced a line of code once and not be any better prepared than if you watched YouTube and practiced your own project. This course prepares you only to look everything up on Stackoverflow. If you want a course that drills into you the language so you have a base level of proficiency, skip this.

DON'T DO THIS COURSE if you are not patien enought! There are many side issues and they're so hard to debug. Everything runs well in the local program but the assignments and autograder per se are troublesome.

More so, the lecturer does not explain anything that should be part of the course (not just prerequisites). I don't know why this has high ratings. Don't be fooled. This course (or even the whole specialization) does not match the previous courses on Python programming. Really disappointing.

This could be an excellend course, but there are some major errors in the assignments that cause students to fail even when the code works perfectly. The problem seems to have something to do with file pathways in the online environment that the course uses. Unfortunately, the instructors show little interest in solving this problem, and I have wasted countless hours resubmitting assignments in an attempt to get the autograder to work. Bottom line- this course is not a good use of your time!

One of the worst course ever designed. The course name states its an INTRODUCTION to one of the most important field but the assignments were so tough(fine...) and "teaching still worse". No proper materials, background, techniques provided, I felt Dr. Chuck would have done this far better. We are expected to know the A-Z of Bible/Geeta for an INTRO course and At last we are made to read documentation and Stack overflow and tell me what's the purpose of this course then???

I've taken a few courses on Coursera and Ive found this one to the be the most frustrating. The assignments absolutely do not match up to the material taught during the week, the questions asked during the lectures presumes we have a lot of base knowledge or wants us to look up the answers but does not give us nearly enough of the language to do so. I absolutely feel defeated after trying to do the assignments and find the forums and "community" to be less than helpful.

While this was one of the better courses I've done on Coursera, the start date of the course was changed without any indication of when it would begin. We've also been waiting months for the next course in the specialisation to begin, again without any communication. This was a good course, but I would recommend people wait until all the rest of the courses are available before starting this course and beginning the specialisation.