Machine Learning with R

Course Details

Machine Learning with R is designed for professionals seeking practical, real-world experience applying R to machine learning challenges. This course goes beyond theory to equip learners with the skills needed to build, test, and deploy predictive models using real datasets drawn from industry scenarios.

You will master R programming for machine learning by following a complete workflow—from data preparation to prediction—while developing hands-on projects that demonstrate your ability to turn raw data into actionable insights. Topics include classification, clustering, churn prediction, and model selection, ensuring you can choose and apply the right approach for varied business problems.

By completing this course, you will gain practical machine learning experience using real-world data, develop applied R programming skills, and understand the end-to-end machine learning process. You will build portfolio-ready projects that prove your ability to solve problems such as classification and clustering, demonstrating job-ready knowledge aligned with industry expectations and setting you apart in a competitive field.

This course includes the following features:

• eLearning resources – exercises, quizzes, flashcards and a glossary.
• Video lessons
• Hands on labs

Who should complete this course?

• Data Analysts and Scientists: For professionals looking to enhance their ability to build, test, and deploy predictive models using R, applying techniques like classification, clustering, and churn prediction to real-world datasets.
• Statisticians and Researchers: Supports those wanting to translate statistical knowledge into practical machine learning solutions, developing hands-on projects that showcase applied modelling skills.
• Business Intelligence and Analytics Professionals: Helps analysts learn to turn raw data into actionable insights, equipping them to choose and apply appropriate models for varied business challenges.
• Developers and IT Professionals Entering Data Science: Provides a structured pathway for those moving into data science roles, teaching the complete machine learning workflow in R from data preparation to deployment.
• Career Changers Building Data Science Portfolios: Suitable for anyone looking to transition into machine learning, offering portfolio-ready projects that demonstrate job-ready skills valued by employers.

Entry Requirements / Prerequisites

• None.
• View the technical requirements for accessing CMIT eLearning.
• Learn more about the suitability of this course.