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Introduction to Data Science in Python, University of Michigan

10,323 Bewertungen
2,444 Bewertungen

Über diesen Kurs

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....


von AU

Dec 10, 2017

Wow, this was amazing. Learned a lot (mostly thanks to stack overflow) but the course also opened my eyes to all the possibilities available out there and I feel like i'm only scratching the surface!

von SI

Mar 16, 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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2,381 Bewertungen

von Oj Sindher

May 20, 2019

This course is highly recommended, as after completing this course you should be ready to analyze your data, clean your datasets, and manipulate it. Also, it includes hypothesis testing, which you can apply on any data-sets to get answers to many insightful questions for that data.

von Nazarenko Oleksandr

May 19, 2019

Thanks a lot!

von Sahrul

May 19, 2019

a great course for beginner

von Sasmit Agarwal

May 19, 2019

This course really helped me learn the basics of pandas.

von Ives Liao

May 19, 2019

Great course!

von Avi Rastogi

May 19, 2019


von Gan Cheong Weei

May 19, 2019

i find this to be a great follow up from the Python for Everyone course. The course introduces python functions which are commonly used in data analysis and the course assignments are practical and useful.

von Irene Liberali

May 18, 2019

Good introduction to pandas/numpy. Requires some programming knowledge. Overall I would have liked more guidance during the videos or through course materials, assignments require a lot of self learning (mostly searching through pandas documentation and stack overflow). However the discussion forums are helpful and the assignments are very well designed to guide the student through learning the basics of data science.

von dhruv_999

May 18, 2019

The Course is well designed for intermediates and level of assignments is also good!

von Henrik Fessler

May 17, 2019

The difference between exercises and lectures is too big. You end up researching elsewhere more than just follow the course.

Exercises being graded is a challenge > installed grader version is different (older) than the note book. This led to the point that my exercises weren't graded due to exception because I used a more recent feature of Python Libraries

Week 4 programming assignment was a challenge: To pass the final question you need to figure out the previous questions as well, other wise you do not get the right answer. In case you got it wrong it is near impossible to figure out the root cause (because the grader doesn't give you elaborate clues where you might correct things). You do not get enough side information on your own so as to solve any issues on your own.

The content covered in the specialization would exactly be the things I'd want to learn, but the learning experience was full of bumps ...probably I won't follow up on the next courses of this specialization.

I heartily recommend an overhaul of this course, giving learners some more background by more explanation & providing more consistent information to master programming exercises.

On the positive side: Staff was helpful for a couple of open questions,. Even as the learning experience wasn't as good as anticipated I learned quite some Python stuff due to the contents of the course.