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4.5

12,109 Bewertungen

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2,811 Bewertungen

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....

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 .

Jan 01, 2017

To be an introductory course I struggled a lot, is a very practical course, and the assignements encourage you to learn more. This is the best technical course I have taken. Lo recomiendo ampliamente

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von Srikrishna M

•Jan 21, 2019

Great course and mentors are very helpful

von Ramya K

•Jan 21, 2019

While this is not an easy course for beginners to python programming, I found it enormously helpful. You'll need to consult other resources to solve the assignments but that was the best part of the course. The assignments taught me much more than just the lectures. Dr. Brooks is a little too fast but you'll adapt tot he pace eventually.

von felixong85

•Jan 21, 2019

It is quite challenging, I think learner with moderate initiative / motivation might not be able to complete this course. There lots of Googling and Stackoverflow needed to solve almost all assignment, especially 3rd and 4th one.

von Sandra D

•Jan 10, 2019

Many of the questions in the Assignments were written in a confusing manner thus requiring a LOT of time to figure out what the request was. However, the WHOLE course and the learning was absolutely outstanding. Thank you for putting this course together and the Forum information that helped to figure out the Assignments.

von JJ C

•Jan 09, 2019

This course has allowed me to improve my data analysis skills and I have already been able to use many of the lessons learned to create more insightful and efficient reports at work

von Arram B

•Jan 10, 2019

Learnt the Basics of Data Science with Python with this course

von Seema a

•Jan 12, 2019

Excellent Learning platform for beginners in python.

von Neel G

•Jan 12, 2019

Excellent Course curriculum

von David A D V

•Jan 22, 2019

I

von TAFSIRUL H N

•Jan 22, 2019

This course is very Useful for the student who wish to start there carirar In the field of data science , This is one of the great course that help the student to learn

von Anirudh J

•Jan 23, 2019

USEFUL

von Shubham C

•Jan 24, 2019

Very nice!

von Oumaima D

•Jan 24, 2019

c'est un cours enrichissant il y'a beaucoup de chose à savoir mais bon en générale il est géniale

von Ian S

•Feb 08, 2019

I enjoyed the course immensely, and learned a great deal. The week 4 assignment is particularly satisfying to complete successfully.

von Yufu C

•Feb 08, 2019

Very well put together.

von Brandon V

•Feb 09, 2019

Excellent for anybody who has to manage large amounts of data on a daily basis. I'll admit that the first week I thought, "Whatever, I can do all of this in Excel." Once I got the hang of it, I realized the potential of this material is unmatched, and I started using Python/pandas/NumPy at our machine learning lab to help us with data acquisition and sorting.

von Zhenwei Z

•Feb 09, 2019

It's a great Course, covers a lot of stuff. It seems that the content allocation between lectures and homework is not well balanced. The lectures are quite short and fast, and the homework are heavy.

It would be great if the lectures can cover more details, especially the techniques that are used in homework. Also the if the homework can provide more instructions and descriptions and maybe some self-checking hints, it would be very helpful.

von Michael M

•Feb 10, 2019

Challenging fast paced course that requires you to do a lot of self-learning. I learned a lot.

von Shashidhar s

•Feb 10, 2019

Very good course for any level data scientists. Prof. Brooks teaches from basic concepts to advanced level very well and in a neat way that no other teacher can. This course covers pandas, numpy, stats, hypothesis etc with programming examples.

von Shreyashi G

•Feb 12, 2019

This course is a high level and precise introduction to the python programming skills necessary for any data analysis exercise. It is adequately paced which is great for anyone who has some prior knowledge of python. The assignments are particularly challenging which I thoroughly enjoyed. The lectures would effectively introduce a concept and the assignment to follow would test the understanding thoroughly - a structure which in my opinion worked great!

von Himanshu s

•Feb 12, 2019

good

von Manish B

•Feb 14, 2019

Good Course

von Tom S

•Feb 15, 2019

A great introduction course of getting familiar with pandas.

von Tianxiang X

•Feb 16, 2019

High-quality lectures and exercises. True to an "Intermediate" course, trusts that the learner will figure thing out themselves and doesn't spent extraneous time hand-holding.

von Vinayak

•Feb 16, 2019

Awesome course for anyone looking to venture into the field of Data Science. The instructor puts forth various concepts lucidly and concisely without any irrelevant extraneous details. Beware though, if you are pursuing this for the sake of learning statistics, you might be disapppointed. The instructor adopts more of a tool-based approach teaching you pandas to solve your problems the way you want to. That said, kudos to Coursera and U Michigan for putting this course together.