Exploratory Data Analysis for Machine Learning

 

Build your subject-matter expertise

This course is available as part of multiple programs,

When you enroll in this course, you'll also be asked to select a specific program.

Learn new concepts from industry experts

Gain a foundational understanding of a subject or tool

Develop job-relevant skills with hands-on projects

Earn a shareable career certificate

Join Free:Exploratory Data Analysis for Machine Learning

There are 5 modules in this course

This first course in the IBM Machine Learning Professional Certificate introduces you to Machine Learning and the content of the professional certificate. In this course you will realize the importance of good, quality data. You will learn common techniques to retrieve your data, clean it, apply feature engineering, and have it ready for preliminary analysis and hypothesis testing.

By the end of this course you should be able to:

Retrieve data from multiple data sources: SQL, NoSQL databases, APIs, Cloud 

Describe and use common feature selection and feature engineering techniques

Handle categorical and ordinal features, as well as missing values

Use a variety of techniques for detecting and dealing with outliers

Articulate why feature scaling is important and use a variety of scaling techniques

 

Who should take this course?

This course targets aspiring data scientists interested in acquiring hands-on experience  with Machine Learning and Artificial Intelligence in a business setting.

 

What skills should you have?

To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Calculus, Linear Algebra, Probability, and Statistics.