Machine Learning Fundamentals in R

Yes, this track is suitable for beginners. Working through this track, users will gain a comprehensive understanding of the basics of machine learning such as how to process data for modeling, how to train models, evaluate their performance, and tune their parameters for better performance.

This track uses the R programming language.

This track is beneficial for individuals interested in jobs such as data science, machine learning engineer, and artificial intelligence specialist.

This track will provide users the foundational knowledge for using machine learning in a variety of scenarios. Users will be able to understand and leverage the principles of supervised and unsupervised learning, creating and visualizing models, and understanding and tuning their parameters.

This track typically takes 24 hours to complete as it consists of several courses.

A skill track typically consists of a series of courses/content that teaches users a specific domain-specific topic/skill from start to finish. In comparison, a career track typically involves a set of courses/content that teaches more advanced topics and subjects, which are geared towards professional development and job readiness.

No, this track is specifically designed for the R programming language.

This track covers predicting categorical and numeric responses via classification and regression, and discovering the hidden structure of datasets (unsupervised learning). It also teaches users about how to process data for modeling, how to train your models, how to visualize your models and assess their performance, and how to tune their parameters for better performance.