0381 - Supervised Machine Learning

Course Description

Overview 

Supervised machine learning is one of the most commonly used machine learning paradigms, as it can be used to leverage existing datasets to draw outcomes that support data classification and predictions. For those who want to stay ahead, innovate, and make more informed recommendations at work, supervised learning skills are key for tackling a broad spectrum of machine learning projects.

This eight-week course uses the programming language Python to provide you with a comprehensive introduction to supervised learning without overwhelming technicalities. You will gain practical, hands-on experience properly implementing and evaluating supervised learning algorithms to draw relevant insights and solve problems.

During the course, you will explore the supervised learning tasks that are used to classify and group data or predict outcomes in real-world situations. Upon successful completion of the program, you will have an expanded machine learning portfolio that you can use to demonstrate your skills for potential employers, and foundational knowledge of the most popular and common supervised machine learning techniques.

Who Should Enroll 

• Current or aspiring data analysts or data scientists looking to build a machine learning portfolio.
• Data professionals looking to add machine learning techniques to their domain.
• Individuals with basic knowledge in programming and mathematics who want to expand their machine learning knowledge and skills.

What you will learn 

• Identify when to use different supervised learning tools and techniques to solve real-world problems with data categorization and predictions.
• Use regression methods to analyze labelled data and make predictions.
• Sort data into groups using classification methods.
• Measure how well your classification models work using different techniques and metrics to draw effective insights.
• Improve your models by selecting the most important variables using feature selection methods.

Course Details 

• Expert instruction from University of Waterloo faculty.
• Learn at your own pace with weekly independent online learning and hands-on exercises and come away with a machine learning portfolio that demonstrates your skills.
• Optional drop-in sessions twice weekly via Zoom where you can ask questions and receive instructor support on key course concepts:
  • Wednesdays, 2 - 2:30 p.m. ET
  • Wednesdays, 6 - 6:30 p.m. ET
• Access to online discussion boards.
• Approximately five hours of your time each week.