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Learner Reviews & Feedback for Introduction to Data Science in Python by University of Michigan

4.5
stars
26,559 ratings

About the Course

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....

Top reviews

PK

May 9, 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

Sep 28, 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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3626 - 3650 of 5,823 Reviews for Introduction to Data Science in Python

By Aditya V

Oct 2, 2019

A good course to start Data Science. However, it would be better if the videos could be more explanatory. This course has very short videos and assumes that the candidate should do EVERYTHING (in terms of research on external resources or reading elsewhere). The assignments are challenging enough for you to learn the technology pretty well but again, there could have been better, longer and more in-depth explanations to cover the assignments. A lot of time goes in doing your research.

By Maximiliano F M

Mar 2, 2021

Muy bueno curso para entender sobre los fundamentos del manejo de datos con python. Los videos son de una alta calidad y hay harto material adicional interesante. Una parte importante del trabajo es de exploración en recursos de internet, pero sabemos que eso es parte de la pega de un programador/cientista de datos y el curso te impulsa a realizar esto. Eso si la tarea de la semana 3 fue muy extensa en comparación con las otras semanas y eso me hizo perder la motivación en un minuto.

By Dheerendra P

Dec 8, 2020

I found this case to be incredibly useful in helping me understand the data analysis techniques using Python. My suggestion would be that the week 1 and week 2 assignments could be updated to have multiple simple questions around various methods to be applied for selecting, inserting, transforming data frames and series. Also, more assignment questions could be included for numpy. Week 3 and Week 4 examples were identical to real world problems data scientists face when merging data.

By João P

Mar 24, 2017

The video classes are informative and very clear. The exercises during the classes were thorough and allowed me to apprehend the concepts at a good pace. My only problem were the auto-graded exams. Sometimes the questions are not crystal clear and the auto-grader isn't intelligent enough to discern between a logical mistake and some detail about table formatting. Fortunately these problems are discussed in the forums and usually one can get clues on what they can be from the mentors.

By Waldo A F

Jan 10, 2022

The contents and the method of transcribing as they are taught was really great

I am not sure I liked some of the assignments though, I spent a lot of time trying to find the number the autograder is looking for, not quite missing the coding part but the wording of the questions

It'd be nice to actually have the results that are being sought or something along those lines like in the previous course

Other than that, very good support from staff, they are clear, patient and responsive

By Ben B

Nov 10, 2020

Overall, a good introduction to data science. You need some prior experience with Python and statistics - otherwise the course might be a bit hard. If you have these prerequisites the assignments are not too easy and not too hard. I especially loved the auto-graded jupyter notebook assignments.

What I did not like are the quizzes. These are done using the UM-website and you get your grade for a multiple choice quiz 24 hours later without any feedback (at least I could not find it).

By Manuel O A

Apr 6, 2020

Even when I have experience with python, sometimes I feel explanations of pandas functions where not explained with enough dedicated time. Some questions in the homework have ambiguous parts, difficult to interpret. The autograder has technical problems to grade answers. Some information would be very useful to have in the instructions of the assignments, not located in the forums.

I liked a lot the examples themes, ie. energy and economics. Videos are very easy to comprehend.

By Vinodhraj M

Sep 27, 2019

Loved the course. Thought it did not teach every technique needed to complete the assignment, it definitely gave directions how to complete it. The forums were very useful to submit assignments. The assignments were quite challenging and interesting. It taught me ways to manipulate data. I started looking data in a different sense now and understand how much information we can mine from a boring looking data. I believe I will be able to apply the knowledge in my job. Thanks much

By VAIBHAV P

Jun 6, 2020

It was my first online course and I liked the content of this course. It was really easy to grasp the concept of series, dataframes, and their methods and attributes. After completing the course, I have got an idea of how the data is manipulated and organised in order to meet certain requirements. The only thing I do not like about the course is that it does not offer a sufficient number of practice problems related to the topics taught. Otherwise, it was a great experience.

By Michael E L

Aug 27, 2017

Tough without some prior knowledge of data science in python. It will take you a lot of on your own research, debugging, and looking up techniques, which is fine, but I feel not a great "intro" course. I need a better foundational understanding of pandas and numpy and still barely know why I did what I did, just that the syntax I managed to find works. Both numpy and pandas are quite powerful and its easy to see their usefulness, but I would call this an intermediate course.

By Mauro B

Mar 5, 2017

A very interesting and useful course for those who want to learn how to clean data in Python.

I loved the opportunity to work directly on the notebook as I was listening to lectures.

I think that more emphasis should have been put in the pros and cons why and how of using the pandas lib. functions in order to accomplish tasks.

Assignments were very instructive and well explained by staff in the Discussion Forum

Many thanks to the staff and to U. of Michigan for the course.

By Zee

Oct 11, 2020

PROS:

1) Course demands students to perform their own research for answers, which is how it is in real-life.

2) Good Assignments, which make you think.

3) Helpful mentors on discussion boards.

CON:

1) Poorly worded assignments, evident by the number of clarification questions posted on the discussion boards. Much time could have been saved if detailed instructions were part of the assignments.

2) Version issues with Python version for autograder versus my local machine.

By Giovanni S

May 6, 2020

The course is really based on a hands-on approach and the instructor expects you to navigate though different sources (books, stackoverflow etc) to deepen your knowledge throughout the program. Maybe video contents could be more detailed and focus should be a little less on self-study. Assignments can be quite tough (sometimes too much) but are also helpful in better understanding the subject and how to 'play' with Python programming. Discussion forum very useful.

By Bilal A

Feb 26, 2017

I found that the videos weren't entirely helpful when tackling the assignments. I had to outsource most, if not all, of my inquiries to external sources (read: stack overflow). Even simple things such as advanced indexing, such as multi-indexing, was unclear. I understand that not everything can be covered, but I feel that basic things should be. Other than that, I enjoyed using the Jupyter notebook, and thought this was integrated very nicely into the coursework.

By devansh m

Jun 18, 2020

It was a good experience. Learned a lot of things and assignments really gets your brain to work and explore. But, sometimes, a bit more of explanation would have helped for assignments. Like, for me personally, understanding 'for' and 'if' loop was difficult to get as it was used almost everywhere. For, that i had to see other videos and learn from somewhere else. It will be helpful, if more questions to practice will be given before directly giving assignments.

By Sudheer K K

May 4, 2017

Introduction to Data Science in Python is good starter course helped me to introduce to lot of concepts needed for basic retrieval, cleaning and manipulating. But I thought teaching can be little more expanded to give more detailed information. Assignments were good, but some are little complicated for the starter. I appreciate Staffing team in helping to us in all possible ways with approach and expected behaviors, validation scripts etc. Thanks to all Staff.

By CHEN K

Feb 4, 2020

i like the course quite a lot. It is very systemetic and well designed. However, personally i think week four is relatively insufficient. Maybe the explanation of mathematics could be less ( coz those are quite basic math at University) and add more test type and examples. Besides, as for the assignment, I think for some quesitons, the explaination is not clear enough, like in assignment 4 last question, "between start and bottom" includes start point or not?

By ZW

Dec 27, 2016

Quite a fast-paced course, with very quick and packed lectures. Would have preferred the course to be slightly longer e.g. 6 weeks and covering more content. I actually found the style of the coursework to be a plus - though it involved a lot of Googling, this is more reflective of real life, where answers aren't just handed to you on a plate. However, the instructions for the assignments aren't very clear in places, which can easily cause you to become stuck.

By Rui d S

Jul 24, 2020

This course is worth due to its challenging assignments. If you are taking this with no previous knowledge of data science, you will be expected to make a lot of complementary research.

There is definitely room for improvement in the video lectures - the contents are somewhat limited when compared to the difficulty and what is asked on the assignments. The lecture could and should present more examples/problems and how to solve them in the most efficient way.

By Subham R

Dec 15, 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.

By Ramanadha R

Nov 17, 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.

By Manasi P

Jul 30, 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.

By Silvia G T

Nov 24, 2022

I liked this course, it gives a strong introduction to useful data analysis packages like re, Numpy and Pandas. I think it should be used as an integration to other, more structured courses at a university. I loved especially the regex part, because it is really well-structured and helped me reviewing the regex syntax; while the Pandas introduction is less useful because the Pandas package has updated a lot from the date this course was recorded.

By Alberto G M H

Mar 23, 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.

By Mark F

Dec 23, 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.