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4.6

6,464 Bewertungen

•

804 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....

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.

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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von Guray C

•Apr 02, 2019

Thanks...That was very fruıtfull...

von YANAMADALA P

•Apr 04, 2019

gud

von Sonal D

•Apr 07, 2019

Very crisp and informative course !

von Juan P

•Apr 07, 2019

g

von SUSHANT

•Apr 07, 2019

This course give a great introduction to the Python Packages and methodology to visualize the data and also evaluate the Model. This is good introduction course which gives concise understanding of concepts and all important python libraries required to get the job done.

von Shashank R

•Apr 06, 2019

Amazing!

von Brahim A

•Mar 31, 2019

Well appreciated the course and the skill.

Thanks a lot!

von Ian C

•Apr 11, 2019

Some Jupyter Notebook cells seem to be outdated

von Alan G M O

•Apr 11, 2019

This is a great course for beginners!

von Na M

•Apr 12, 2019

We need more practice, projects.

von Sizolwethu D

•Apr 01, 2019

A very engaging course on Python methods, models, functions and tools for Data Analysis.

von Maaz A

•Apr 14, 2019

One the very well defined and finest course I have ever seen

von Felix G

•Apr 15, 2019

Excellent course!!!

von KUMAR B P

•Mar 12, 2019

The course is unique in it's own way, simple in understanding and applying

von 朱晓琳

•Mar 12, 2019

This course is about regression, how to create models, how to evaluate and select a model or parameters. These are exactly what I would like to know.

von Subrahmanyam

•Mar 05, 2019

good

von Yves B

•Mar 03, 2019

Very thorough teaching of statistical analysis using python

von Gurnam S

•Mar 04, 2019

very nice...

von Callistus N

•Mar 13, 2019

The best gentle intro on creating and evaluating models.

von Luciana M G

•Mar 14, 2019

This course is an excellent continuation of the previous IBM ones. Actually there should be one whole course teaching the basics of statistics so that what is taught in this model makes more sense for those who have never studied statistics before.

von Liu C

•Mar 06, 2019

very good course, i now know for about how to analyze data and find the right model for analysis

von Suhas S

•Mar 15, 2019

It is really a Good course. All the topics have been covered in the proper way.

von Matheus L T A

•Mar 15, 2019

Great! Filled with lots of concepts and practical exercises!

von Saurabh M

•Mar 15, 2019

It is a great gateway

course into the world of data science. It is mainly focussed on theoritical concepts of data science which have wide range of applications .

von Vimel M

•Mar 15, 2019

very clear and helpful!

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