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Opiniones y comentarios de aprendices correspondientes a Introduction to Data Science in Python por parte de Universidad de Míchigan

4.5
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25,634 calificaciones
5,714 reseña

Acerca del Curso

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses. This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python....

Principales reseñas

PK

9 de may. de 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

YY

28 de sep. de 2021

This is the practical course.There is some concepts and assignments like: pandas, data-frame, merge and time. The asg 3 and asg4 are difficult but I think that it's very useful and improve my ability.

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5526 - 5550 de 5,665 revisiones para Introduction to Data Science in Python

por Dorian B

17 de abr. de 2022

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?

por Lucian C

24 de abr. de 2020

After having done quite a few other courses from UMICH (mostly taught by prof. Charles), I had high expectations from this one. I must sadly say I am extremely dissapointed.

1) The course itself doesn't teach anything. The videos basically say: "Here's pandas. It has functions. Good luck". If you want to learn what to do, you are encouraged and have to search it online, because such materials are not provided in the course.

In my opinion it cannot be called a course, if all it does it says "Hey, there exists this thing called Python and Pandas. If you want to learn about it, go do it somewhere else. You're welcome! "

A responsible course would provided well strucured materials for students to study. Videos showing a proff. reading off slides are not particularly useful.

2) Assignments are messy and it seems not much thought has been put into them. Whilst I do like the challenge itself, spending 3 hours figuring out why the autograder gave me no points is completely useless and frustrating: you get no feedback, no hints, no nothing. Eventually you may be able to find some hints on the forum, but seriously....those 3 hours could be way better spent on some actual materials, rather then trying to figure out a formatting issue.

I could go into more detail, but you get the idea. I was really excited about this specialization, but I will not continue with it. Again - I've nothing against a challenge - so a more difficult curricula - but I cannot work with a completely lack of curricula and structure , as well as materials.

por Moncef K A B

16 de jul. de 2020

This is not my first time with the University of Michigan, I have completed both the "Python for everybody" and "Python 3 programming" specialisations; and i must say , this is an assignment course, the material is rushed (if you are just talking about 10 pandas methods in an 8 minutes video,; you need to review your pedagogy). Paul resnick , dr.chuck and steve oney are really good teachers, they go into the details.But i don't know if he was forced to , but Christopher brooks doesn't seem to bother with explanations (you should learn everything on stackoverflow; well guess what ...i came to coursera for the material not the assignments).He had already done that in the 5th course of the python3 programming specialisation(sometimes explaining code without showing it),it took me 5 days to complete that assignment(notebooks crashing for no reason i ended up using my own but i guess this has to do with the platform ) .

some more pedagogy and slower ,deeper explanations are required for this course.Not worth the time nor the attention.Just learn on Youtube and Stackoverflow or some other ressources(like the many books provided in this course) then once you are ready, pass all the assignments(which are great ,if the material needed was covered this course would be perfect)

por Steven C

17 de jul. de 2019

This class is an absolutely horrible experience for those of us new to programming and data science. For a few of the assignments, you are asked to return a dataset based on the merging of multiple data sets. A better approach would have been to have a checkpoint at each step to ensure the resulting data frame met the requirements. For example, if the data set needed to be ordered in a certain way with the header formatted a certain way, then let's have a separate checkpoint for the order of the values and yet a different checkpoint for the header values.

The staff needs to understand that having the correct answer at each step of the process is not a bad way to help the student know if his/her code is correct. After all, the staff can easily modify the dataset read in by the student's code after submission to ensure that the student did not use any hardcoded values.

Despite the frustration with the Coursera platform, I can honestly say this is the most fun subject I've had in a long time. But the format selected is absolutely horrific and not conducive to learning and understanding the material.

por Jakob P

20 de may. de 2017

The main focus of the course is the introduction of the Pandas (series and data frames) library, which is very useful in data analysis. The last two assignments are quite challenging and time consuming, if you are not familiar with Pandas. Why the poor review: I'm sure that the intention of the teacher (Prof. Brooks) is for the student to be challenged and obtain familiarity with several "advanced" functionalities of Python. When I had finished the last assignment I felt that way, but not due to the lectures (only ~2.5 hours all in all). The pace of these lectures is too fast (probably because they are scripted). The teacher should slow down a bit and show some more examples (for inspiration watch Prof. Andrew Ng from Stanford lecture on machine learning). I'm not suggesting to show explicit solutions of the assignments, but just a few more examples such that the transition from lecture to problem solving is less "frustrating". Furthermore, the students are paying $79 for this course expecting thorough lectures on the topic. Reading the documentation of the Pandas library can be done for free...

por Stephanie R

16 de jun. de 2021

The format of the presented material - essentially a live transcripting of the lecture - was not a very helpful way to present the information. I would rather listen to the words, rather than wasting space having them written out, and have longer to study the code snippets. An explanation of what each of the code snippets is doing would also be enlightening. And the lecture material didnt really relate to the content of the assignments, those had to be solved through self-study. By Week 3 Id given up trying to absorb anything from the lectures and was teaching myself how to solve the assignments using the internet. Consequently, Im not confident that the solutions I implemented are elegant rather than just brute force and ignorance; a model answer or equivalent would be helpful for teaching the idioms of python. I only completed this course because it was a prerequisite for a data science training specialism organised by my company, otherwise I would have abandoned. This course can be summarised as "figure it out for yourself".

por Alisa A

22 de jul. de 2019

Read the reviews carefully before signing up for this course.

I would not recommend this course to anyone. It is branded as an Intro course, but it is anything but an intro course.

The instructor whips right through the material without much explanation as to the how and why of what he is doing. Then when it came to the assignments, the assignments were way harder to the material covered, and I spent hours pulling my hair doing research on StackOverflow and GitHub just to figure out how to get the data sets to work correctly so the auto-grader could pass my problem. I ended up dropping at the fourth week because I knew I couldn't finish the project without referencing other people's work on GitHub and there was very little instruction on how to set up and do the final project effectively.

There have been very few courses in my life that I felt utterly defeated by, and this is unfortunately has been one of them. I am going to pursue other data science courses on Coursera and other resources that are better suited to the beginner.

por Andy F

28 de may. de 2018

Dire, absolutely dire. If you like the following; A. Spending longer endlessly searching the forums for answers than anything else and still not necessarily finding them B. Wasting time getting the right answers only for an autograder to decide an answer that hasn't been touched for an hour and was right, is suddenly wrong (not a great advert for a language you want to use to automate this, is it?) C. Reading countless posts voicing a lot of similar frustrations to this D. Lectures so brief you may as well not bother E. Interpreting "assumes some knowledge of other languages" as "you best be great with these other languages because these lectures won't really help you" F. Wasting yet more time on the forums where answers to one post go totally off track so you're left hunting for a needle in a haystack of replies for something that may or may not be of relevance.

If these things are truly your bag then this is the course for you. If not, then do yourself a favour, go elsewhere and find a different course.

por Todd R

5 de mar. de 2021

I loved intro to python with the other teacher, but not this. Staff is helpful, but the homework is completely different from the course. Assignment four has us using extract with expert level to do the job. My correlation was off . I had .17 , but the answer was .15. Found I missing data or one city San francisco instead of having two. For instance, autograder tells me in question 1 of assignment3 that my columns are named incorrect. I see nothing wrong with them after comparing to the assignment . what does formatting have to do with passing anyhow. I could just cut and paste, rename and submit, but I have to wait a day for the results and my submission is already late. I Getting question 1 of assignment3 is required to get the other questions, so I got sort of sick of it. I learned something certainly, but sick of the frustration. I looked forward to my python and Jquery classes. I don't look forward to data science with python.

por Rohit S

26 de may. de 2020

As a beginner,This Course theory is very good and can be understood with a little of Python Basic Programming skills cuz of the 1st week notebook and theory provided.and coming to the other weeks,the theory was good but short and faster explanations ends you up in a dilemma.I personally feel that this course is highly recommended for the purpose of 'THEORY ONLY' != 'Assignments'. If you want to work on assignments you'll end up loosing your mind,and for the assignments I recommend people to just checkout Stack Overflow or the discussion forums or Github to answer them.Definitely You won't be able to grasp everything in here,so I prefer and refer you people to checkout courses on 'PANDAS' to work explicitly.

por Christopher I

5 de dic. de 2016

I was quite disappointed by the almost total inaccessibility of the staff in the discussion forums, the unconquerability of the autograder for most of the assignments (losing points for no discernible reason, with all resources exhausted), the lack of a stats module for the specialization, and the lack of education, really. There is value in asking students to learn on their own, but this course goes much too far with that, giving problem sets that are virtually unsolvable without prior experience in data wrangling in R or some other data language. This leaves serious, hardworking students with little choice but to troll the forums for solutions. Hardly the best way to learn the intricacies of this subject.

por Kennedy P

9 de may. de 2020

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.

por Ruşen B

1 de oct. de 2021

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

por Fabrizio B

25 de ago. de 2020

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.

por Chris R

9 de abr. de 2021

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.

por Guilherme P d S

27 de mar. de 2021

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.

por Marc C

4 de ago. de 2019

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.

por Jialian Z

16 de feb. de 2022

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.

por Andrés D A C

25 de may. de 2020

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.

por Michael M

25 de may. de 2020

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.

por Devansh K

14 de jul. de 2020

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.

por Jason G

30 de ago. de 2017

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.

por Don S

20 de jun. de 2018

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.

por JOY S

5 de nov. de 2016

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....

por Christiano d S

7 de jul. de 2020

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.