CAC107 - Building Predictive Machine Learning Models

Course Description

In this course, you will explore some of the machine learning tools you can use to magnify the analytical power of Python data science programs. You will use the scikit-learn package — a Python package developed for machine learning applications — to develop predictive machine learning models. You will then practice using these models to discover new relationships and patterns in your data. These capabilities allow you to unlock additional value in your data that will aid in making predictions and, in some cases, creating new data.

You are required to have completed the following courses or have equivalent experience before taking this course:

• Constructing Expressions in Python
• Writing Custom Python Functions, Classes, and Workflows
• Developing Data Science Applications
• Creating Data Arrays and Tables in Python
• Organizing Data with Python
• Analyzing and Visualizing Data with Python

Faculty Author

Benefits to the Learner

• Articulate different types of machine learning problems
• Use the Python scikit-learn package to train models and make predictions
• Use the Python scikit-learn package for unsupervised clustering
• Explore a dataset with machine learning

Target Audience

• Data analysts and business analysts
• Database managers
• Technical and systems analysts
• Programmers interested in data science
• Marketers
• Business managers

Applies Towards the Following Certificates

• Python 360 : Core Courses
• Python for Data Science : Core Courses