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Learn to analyze data with Python. This course will take you from the basics of Python to exploring many different types of data. You'll 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) Manipulating the Data Frame 4) Summarizing the Data 5) Building Machine Learning Regression Models 6) Building Data Pipelines Analyzing Data
Learn to analyze data with Python.
This course will take you from the basics of Python to exploring many different types of data.
You'll 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 data sets 2) Cleaning the data 3) Manipulating the data frame 4) Summarizing the data 5) Building machine learning regression models 6) Building data pipelines Data analysis with Python will be delivered through lectures, labs, and assignments.
It includes the following parts: Data Analysis Libraries - You will learn how to use the Pandas, Numpy, and Scipy libraries to work with a sample data set.
We'll introduce you to pandas, an open source library, and use it to load, manipulate, analyze, and visualize interesting data sets.
Then we'll introduce you to another open source library, scikit-learn, and use some of its machine learning algorithms to build smart models and make interesting predictions.
If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.
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