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

22,779 calificaciones
5,107 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

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

15 de mar. de 2018

overall the good introductory course of python for data science but i feel it should have covered the basics in more details .specially for the ones who do not have any prior programming background .

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3101 - 3125 de 5,030 revisiones para Introduction to Data Science in Python

por Subham R

15 de dic. de 2019

Nice course to learn data science. I learn a lot of new thing about data science, different python packages used for DS. I felt like week 3 and week 4 assignment were a bit difficult and video lectures should have been in more details and assignments should be more related to the video lectures.

One should have coding background in python in order to complete the course assignments without too much difficulty.

Anyway I'm glad I took and completed this course.

por Ramanadha R

17 de nov. de 2018

Feels great, I am introduces to the Data Science in Python. But this was too much of crash course. It needed a lot of homework outside this course - Youtube, Python docs, stackoverflow and some blogs. That work should have been added as part of the course. And those statistics almost went over my head. As I have no foundation in statistics, I may not choose for the next level of course - seeing the difficulty of the statistics it has introduces so far.

por Manasi P

30 de jul. de 2017

This course was illuminating and rich in information. However, I noticed a huge gap between the content covered in lecture videos and the knowledge level needed to complete the assignments, which made the assignments way harder than expected. This might be intentional, in order to prompt students to explore the full functionality of python and take advantage of online documentation. Overall, this was a good course to really get my feet wet with python.

por Alberto G M H

23 de mar. de 2019

This is a great course for those with some Python background, as the professor clearly states at the first lecture. This was not my case but since we were a team of friends we could solve all the homeworks. If you have not taken an introductory course in Python, neither you have a group of friends to work with, then I suggest you not to take this course. Otherwise, It is a great opportunity to explore advanced Python data analysis techniques.

por Mark F

23 de dic. de 2017

Overall I thought this course was good quality. The videos and lecture material were informative. My only constructive suggestion is that that code is shown too briefly and moves on to new functions too quickly to absorb. The instructor participation in the forum was essential for being able to complete the assignments. But overall I thought this was effective in getting me to learn some Python independently and I would recommend it.

por Andrey K

23 de may. de 2020

This is a pretty good course to start immersion in data science. Lectures are very compact and without extra water. Links to books and additional resources are provided. You can get support from teachers in the comments on lectures and assignments.

At the same time, the course requires updating in accordance with the latest version of pandas. During the course, I was faced with the need to rewrite my code to satisfy the old version of pandas.

por héjer s

4 de abr. de 2020

J'ai appris énormément avec ce cours et je remercie les professeurs et tout le staff ainsi que tous ceux qui ont participé dans le forum et qui étaient d'une aide précieuse.

Cependant je trouve que plusieurs questions sont mal posés et une grand partie de mon temps je l'ai passé à essayer de comprendre ce qui est demandé.

J'espère que les questions seront mieux posés et que l'effort sera consacré à l'apprentissage de nouvelles techniques.

por K. Y W

29 de may. de 2017

Tough course for a "Introduction to..." course title. Good support resources saved the day. Learnt from doing the assignments and following the tips from the teaching staff. Very practical assignments. Gave a flavor of what data science work involves. Challenging and engaging. The course videos are very well produced. Prof. Brooks is motivating and energizing. The course also gave a human dimension to the work of data science. Thank you.

por Eric L

7 de ene. de 2020

I enjoyed the course, overall. The assignments were challenging and required some help via stack overflow, but they were do-able and not impossible. The notebooks are great for experimenting and self-learning, but the lectures didn't go into enough depth, for my liking. In addition, the speed of the lectures was too fast on many occasions. I'd recommend having some programming background and/or familiarity with Python before taking this.

por Bernardo S L e B

4 de ago. de 2019

The course has indeed taken place over much of what can be considered introductory in data science. However, there is nothing introductory about python, which may bother a more novice student, and the second week of the curos is much more challenging than the others. I believe it is possible to build this same course in 5 weeks to teach more about python and reduce the difficulty of the second week without compromising depth and quality.

por Jared P

7 de mar. de 2017

This course is difficult. It stresses a lot of core skills in pandas and python. I wish there was more instructor support for the times that code just doesn't seem to match up with the grader's expectations. There is still a question in the course that I am relatively positive I answered correctly yet did not receive credit. Overall, the format is incredibly well done and the use of Jupyter notebooks makes the tasks very approachable.

por Dustin H

20 de ene. de 2017

I learned in this course that pandas is a way deeper rabbit hole than it appears on the surface. However rather than teaching me pandas this course mostly just helped me verify that I was learning pandas. The questions in this class need more scaffolding. I ended up skipping most of the in-video questions because I felt that the work I was investing in getting them correct was not teaching me much. More scaffolding could fix this.

por Terry A W J

29 de dic. de 2016

As compared to some other machine learning/data science courses offered "Introduction to Data Science in Python" was very pragmatic. Starting out with simple data cleaning and data structuring may not be the most exciting thing ever, but it was extremely useful to learn the basic tools needed to be a competent data scientist. One point of warning - the homework and projects took me about twice a long as suggested by the course notes.

por Carlos V

26 de nov. de 2018

Introduction to Data Science in Python is a challenging and rewarding Course, the instructor explanations are excellent, and the recommendations in relation to best practices utilizing Python, Pandas and Numpy are super valuable, the assignments are super challenging in particular because of the auto-grader and the substantial amount of pre-processing of data required for the assignments so book extra time to complete this Course.

por Hal S

27 de nov. de 2016

Lectures clear and well-organized. Homework needlessly complicated and with large gap from lecture material. Grader did not give enough info when rejecting submitted work. Weighting last problem at 50% of final week was unpleasant. Hosted platform allowed importing re and io.StringIO, but grader rejected them. Hosted platform had consistent kernel failure on my last solution, but it worked on another system and grader accepted it.

por Gowri T

27 de jun. de 2019

The course was challenging and the assignments well thought of. While I appreciate that a lot of learning was left to be done on stackoverflow with the intent of making us self reliant, a lot of us are already used to those forums and gathered around this course so information would be available in a centralized manner and time spent searching online could be minimized. I think the course designers totally did not get that point.

por Tarun S

25 de may. de 2020

I learned a lot about data handling and manipulation in python, pandas and NumPy. But I feel the course instruction was too fast to follow up, even to a python coder like me. The course expected one to learn a great deal of part from your own rather than relying on the video lectures. The assignments and quizzes were very challenging, pushing you towards your best. To conclude I think the instruction couldhave been much better.

por Pascal M

18 de nov. de 2017

Before Machine Learning comes a lot of Human Action. This Data Science course provides a solid basis for understanding and learning the inner works of manipulating very large datasets in Python. Besides the technical aspects I was pleasantly surprised to read and think about the ethical sides as well. I would rate this course 5-star if some exercices were better phrased or if more examples to make some exercises more manageable.

por Mohit S

21 de nov. de 2018

A nice course to kick start Data Science. Doing the assignments will improve the learning and will boost the confidence about the topic. Tutor, TAs and discussion forums are very helpful, so, consult them if you get stuck somewhere. Coursera platform was flawless, course structure was good. But I expected more content would be covered in the course. So, overall it is good course to get an insight into the world of Data Science.

por Martin T

19 de dic. de 2016

After having taken several Data Science-related courses, this course seems like a good introduction to Python for Data Science applications. Not much 'actual Data Science' is covered in the course, however. It's more practically-oriented in the sense that it deals with data preparation (loading, cleaning and merging data). You don't get the luxury of the common perfectly-prepared csv-files in this course, which is a good thing!

por Will G

13 de feb. de 2017

Overall this was a great class. The programming assignments were the most valuable part of the course for me and were good practice for wrangling data with pandas. I did find some of the assignments asked questions in a way that were confusing and it was difficult to debug the answer based on the automatic grader. However, I'm looking forward to when the rest of the specialization is available, as this looks like a good track!

por Robert J K

9 de dic. de 2018

Even though I am already a heavy user of Pandas in my daily work, this course forced me to learn several useful features that I had never knew about or bothered to learn. The exercises were challenging enough that it took a decent amount of time and effort to complete them. There were many technical challenges with the autograder and the coursera hosted notebooks that made this more of a challenge than it should have been.

por Arindam D

23 de jun. de 2018

A great starting point for venturing into Data Science, for students/engineers who have some programming background. In my case I had the basics of Python covered , so it wasn't too hard to catch up.However, for enthusiasts with very limited programming experience.... Beware !!! It will appear to be too fast. My final conclusion .... spend 3-4 weeks to learn Python fundamentals and then enroll .... its very enlightening.

por Awik D

4 de may. de 2020

The lectures seem to be giving the bare minimum description of functions and stuff that makes it hard to understand the intuition behind the syntax and working of, say, a line of code that a given lecture tries to teach explaining how it helps serve a purpose. This, in turn, makes it hard to remember the syntax of functions. The assignments are very useful but take a long time since I barely learn from these lectures.

por Beda K

13 de jul. de 2017

I really liked this course. It gives a good overview of the pandas library and some associated topics. For me, it aligned very nicely with my personal interests. I would have liked some more advanced topics as well, but I understand that this is an introductory course, so it is not in its scope. The integrated Jupyter notebook feature of Coursera is very neat - both for reviewing code from lectures and for assignments.