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Data Analysis with Python, IBM

4.6
2,552 ratings
345 reviews

About this Course

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....

Top reviews

By 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

By KS

Mar 22, 2019

Highly recommended course. All i was about data analysis with using Python as a tool. In this course you can learn basic econometric, python, and of course how to analyse data.

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348 Reviews

By Maksim Mislavskii

Apr 18, 2019

Very serious, professional, empowering course. Clear straightforward detailed explanations. A good deal of practice.

By Nihal Nalla

Apr 18, 2019

not in depth.... needs more clarity on a variety of topics

By Kalpa

Apr 18, 2019

Hands on and practical course, Lab exercises help to drive in the methods

By chengwuquan

Apr 18, 2019

perfect

By Anukruthi Ramachandruni

Apr 18, 2019

Im very interested in this course. Ill let my peers to this course.I'll suggest everyone to make thier skills better.

By Abdul Mujeeb Abdulai

Apr 17, 2019

Not very interactive with fewer help to learners

By Vidya Raghavendra

Apr 16, 2019

Very Math!

By Juan Vicente Peluso

Apr 16, 2019

I think that you missed more detailed explanations on how to analyze the results, especially for those of us who are not mathematicians or with advanced knowledge of statistics. But, is a fact that In the end it was the course i've enjoyed the most. This is awesome

By Santanu Basu

Apr 16, 2019

Not a great course. Sometimes it is too fast and the explanations are very short. More hands on exercises would have been more helpful.

By Teofilo Estevam de Araujo e Silva

Apr 16, 2019

Too complex for easy understand. Should have some documentation explaining the process and comparing the new methods.