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4.6

3,025 Bewertungen

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394 Bewertungen

Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more!
Topics covered:
1) Importing Datasets
2) Cleaning the Data
3) Data frame manipulation
4) Summarizing the Data
5) Building machine learning Regression models
6) Building data pipelines
Data Analysis with Python will be delivered through lecture, lab, and assignments. It includes following parts:
Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions.
If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.
LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

von RP

•Apr 20, 2019

perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.

von OA

•Jul 13, 2018

I have been looking for a very non-complicated course on data analysis and I hit the Jackport with this course! Very simplified and explanatory. You should definitely take the course

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396 Bewertungen

von Amy Peniston

•May 19, 2019

I am working through the IBM Data Science Certificate courses (in order) and this is easily the best one I have taken so far. Once again, the labs provide a variety of hands-on exercises that help to cement the topics introduced in the lectures (which, to be fair, are very fast-paced). Everything taught is practical and relevant. One request would be to fix the pacing of the videos and lecture quizzes, which often appear to test students' comprehension mere seconds after the topic was discussed! I did also notice a few errors in the labs, but they did not stop me from learning the material. Overall, great course.

von Theodore Griesenbrock

•May 19, 2019

This needs to go much more in depth on the options for analysis, and provide more examples.

In addition, the labs and final exams were not fully completed/corrected/reviewed, so there were many erroneous issues, including assumptions made that was not clear to us students.

von Sampras Ghosh

•May 19, 2019

best course for beginners

von Firat Gunduz

•May 18, 2019

A seriouse deal of statistical modelling taught with a perfect content. I really appricate the effort put in order to not being "hard-to-understand", but still finding the way to teach complex statistics. You will have a very good useful knowledge of statistical modelling without getting lost through too many greek symbols and long explanations.

von Aditya Jha

•May 18, 2019

None

von Deepak Panchal

•May 18, 2019

The Content was really good but some topics are explained in very short.

But Thanks for this awesome course!

von Sifat Sharmeen

•May 17, 2019

I find this course useful. But some of the contents are little advanced all of a sudden and feels some important explanations are not covered.

von Robert Phung

•May 17, 2019

Some concepts were quite confusing and not that well explained.

von Maciej Laskowski

•May 16, 2019

Too many complicated things happening at once. It is hard to digest and follow.

von Chimi Charles

•May 16, 2019

was really nice

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