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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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25,917 calificaciones

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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4976 - 5000 de 5,723 revisiones para Introduction to Data Science in Python

por fabien M

7 de jul. de 2020

I have mixed feelings.

1) the course is very interesting. It is an applied course, there is a lot to learn.

2) But very hard too. There are so many things, that you may have difficulties to memorize quickly through practices. Then, you end up roaming on stack overflow and pandas documentation because you just can memorize enough to process and have to rely heavily on the documentation.

If you are interested to dig into the python, this is very interesting (but quite hard)

por Alexandre M

10 de ene. de 2019

This class definitely makes you learn, but not as much from the lectures and course materials themselves, as from the discussion forums (shout out to teaching staff and mentors for their great help) and online tools like Stack Overflow.

I understand that this is also a technique to make us more independent, but it seems like the professor just wanted to skim over this part in order to concentrate on some future / more advanced class that is more interesting to him.

por Thomas L

22 de ene. de 2017

Although I learned a lot in this course, I found the lectures and assignments to be much too different from each other. I would like to see assignments where you must practice what is learned in the lecture. For myself, I feel I learned 1 set of concepts from the lectures and another set from the assignments by spending time on stack overflow and the pandas documentation. Both are good but the lectures and assignments did not "flow" together as I would have liked.

por Aram H

13 de nov. de 2016

The course is very interesting. The Jupiter notebook is very useful.

I don't like that many examples are very US-specific. Some important terms may not be clear for people who live outside USA.

Update: I'm lowering my grade from 4 stars to 3 stars because of very confusing assignments. Often it's not clear the requirement of the task. It takes very long to understand. Also some assignments require methods and functions that were not covered in video lectures.

por Saurav K

13 de ago. de 2020

course content is good,but the instructor tries to explain everything just by saying it. does not demonstrates it every time and does not dive deep into the concept,so that the learner may get more interested. and if you are stuck at any assignment question then it might happen that you won't get the answer even after seeing the videos. assignment contains some questions based on concept which are not discussed,so you have to figure them out yourselves.

por Pedro G d B R

2 de abr. de 2020

Excellent lectures and explanatiom about Pandas features. But the Assignments could have more conection with the lectures of the correpondent week. Also the instructions to code the assignments are often bad written or lacking information, causing erroneus comprehension about what are being asked. These kind of problem cause a lot of misconceptions abou the task and cost a lot of time from the student just to really understand the assignment objective.

por Pascal V

3 de feb. de 2020

The assignment of week 4 is wrongly explained in the jupyter notebook. It says that the price_ration is equal to quarter before recession divided by quarter bottom recession. When you do so you will never get a validated result. The only result validated is recession_bottom minus recession_start!

Giving assigments should include expected solution. Now you upload your file several times in order to figure out you are using the wrong formula.

por Jordi C

29 de dic. de 2016

In my humble opinion, this course does not have a correct balance of difficulty of new concepts/tools with the exercises given by the course to practice. It is a "hey, look, there is something called pandas out there that may be very useful for you" but it is too introductory. And I know the course has the word "Introduction" in the title but that does not grant, in my opinion, to run a 4-week course such as this one with so little content

por Alvaro A

4 de mar. de 2017

The whole curse relies on the automated grading system, which is still a little sloppy. I think it would be useful to have one notebook or cheatsheet with all the important functions. And also, I personally like to have a reference assignment that was completed by the instructors. This could be provided before or after the course, but the way I really learn is by reading other peoples code and seeing ways to code problems. Thanks

por Chyld M

16 de nov. de 2016

A good introduction to python and data science. The questions were just about the right level of difficulty. My main criticism is that the online videos were pretty short and not going into a lot of detail, whereas with the questions you had to do a lot of extra research to figure out how to solve them. More interaction with the enrolled students during the course and having more in-depth videos would make the course a lot better.

por Shivam S

14 de jul. de 2019

The course is good if you are carrying even a little experience with python and data science. The teaching methodology is not that impressive but it can make key points clear. Assignments are really good which can be the best part of the course undoubtedly. Though once enrolled, you will yourself going through the discussion forums a lot because not everything is provided for the assignments. Self-exploring is highly encouraged.

por Dr S K

24 de dic. de 2018

The material intended to be taught by this course is really good. What is missing is additional video tutorials to support the learner. I had to resort to youtube video by codebasics and other people so I could put together the required knowledge for this course. It urges the learner to do individual learning which is good, but there needs be more direction and support with educational material presented in a meaningful manner.

por Soham A

14 de jun. de 2018

The assignment questions need a thorough understanding of the concepts which requires elaborate explanations with more examples. I felt that the standard of the examples were too low as compared to the standard of the assignment questions. I would not recommend this course to any beginner of Python language. The discussion forums on the other hand are inactive and I haven't received any quick response to my questions posted.

por Rolf B

21 de feb. de 2018

Overall I learned a lot, but the relation between course material and effort to pass the assignments is not good. For example for week 4 there is 23 minutes course material (videos) and I needed roughly 15 - 20 hours to pass the assignment. In week three it was not much better.

The videos are only describing rough principles. For the assignments you have to search for a lot of other sources in the internet.

por Brent A

12 de feb. de 2017

In my humble opinion, the Python ramp-up in week 1 is not sufficient to effectively complete weeks 2-4. This course necessitates a bit more practice in Python. The lectures are cut-and-dry, and I recommend frequently referencing them when completing the assignments. I spent about 1.5x the listed time-to-complete on most assignments. On the flip side, I gained a lot of knowledge by putting forth full effort.

por Ryan S

1 de mar. de 2017

Honestly, it was a good crash course into data science in python. My 3/5 star rating comes from the fact that I think their could be more content / examples shown in the videos. The videos were a good start into the assignments, but I had to spend hours reading on the internet to really understand enough to complete the course.

I liked what I saw in the videos, just wish there was a little more substance.

por Carlos A R F

11 de oct. de 2021

There are good explanations about Numpy and Pandas, but the assignments are unnecessarily difficult and you will require to look up more functions and methods (that were not previously explained) to finish the course. (I consider that this is an inefficient way of learning)

Also, this is not an introductory course to data science in Python, it tries to cover a lot of topics with Pandas and Numpy.

por adam

17 de feb. de 2017

Course lectures were good, tho at times a little too rapid. The python text appears and disappears too fast to digest, I did a lot of pausing.

The early exercises were good, but later ones were finicky. I would prefer more intermediate steps to confirm we're on the right track. In particular the last (huge) exercise was frustrating, just being told I've got it wrong with no feedback on why.

por Hani H

28 de abr. de 2022

I'd give this 5 stars but the auto grader is atrocious. Wasted too much time trying to debug instead of trying to learn, and the instructions were never clear, like you could warn me that I need to place all my work inside the function so the auto grader wouldnt freak out, or that I need to delete the raise error once I finish the question

Oh well. I learned a lot, but the assignments were hell

por Etienne B

24 de jun. de 2020

The content is rich and useful, but the assignment in week 3 was excrutiating: it was too long with pointless, confusing questions. I really considered quitting the course though I already practiced pandas heavily in the past. Please do something about it. The assignment in week 4 was much more profitable. Not necessarily easier, but it had meaningful questions and a concrete goal to achieve.

por Mohamed A

5 de abr. de 2022

the programing assignment were challenging, which is good as it resamples real world problems. However, the lectures were really lacking in terms of content and the student is left wondering around in stackoverflow finding ways to solve the problems. If this was the intention of the course, then you did great, however, for me, I wanted more content and a lot more explaniation in the videos.

por Wanqing S

5 de abr. de 2018

The course material is shallow and there's a huge jump between the lectures and the assignment. I'm able to finish the course only because I learned python and pandas before. The assignment questions are sometimes too vague, and grading system doesn't show why the answer is wrong. It would thus be very helpful to have a option for showing the correct answers after one finished the course.

por Shubham K

8 de sep. de 2019

This course requires a lot of self learning from students, it would have been great if there were more video lectures. I found this one a little bit difficult for me because it required a lot work by my side. The course is okay i will say. It gives a general idea of what this field is all about. I really loved the articles this course provided , they were interesting and informative.

por Adriano H G d S F

17 de mar. de 2021

Para os amigos brasileiros, a semana 3 e 4 é bem difíceis. O curso aborda demais o Pandas, no entanto pra mim só alguns pontos foram úteis, pois não mexo tanto com data frame. Mas é sempre bom saber que existe. O professor é maneiro dá bastante exemplo, porém muitos exemplos não casam com algumas partes das atividades, as vezes você precisa ver a documentação e tals. Mas faz parte.

por Gavin C

10 de feb. de 2018

A decent introduction to data analysis using python, particularly introducing the pandas framework. The material can be a bit uneven and disjointed, and the assignments sometimes leave you guessing what is actually required, but overall this was a useful intro to the topic areas. If you're prepared to supplement the course material with your own research you'll get a lot out of it.