Turning categorical variables into quantitative variables in Python - Data Analysis with Python

Link to this course:
Turning categorical variables into quantitative variables in Python - Data Analysis with Python
IBM Data Analyst Specialization
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.
Predictive Modelling, Python Programming, Data Analysis, Data Visualization (DataViz), Model Selection

Turning categorical variables into quantitative variables in Python - Data Analysis with Python
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