Dive into the essentials of machine learning using R with this comprehensive training. Explore fundamental algorithms and techniques for supervised and unsupervised learning. Hands-on exercises and real-world applications will solidify your understanding of machine learning concepts.

Target Audience

Dive into the essentials of machine learning using R with this comprehensive training. Explore fundamental algorithms and techniques for supervised and unsupervised learning. Hands-on exercises and real-world applications will solidify your understanding of machine learning concepts.

Prerequisites

Data scientists, analysts, and professionals interested in applying machine learning techniques using R.

Outline Course

Introduction to machine learning and its applications Supervised learning: regression and classification algorithms Unsupervised learning: clustering and dimensionality reduction techniques Model evaluation and performance metrics Feature engineering and selection

Outcome

Participants will gain practical skills in implementing machine learning algorithms using R, enabling them to build predictive models, perform data analysis, and make data-driven decisions effectively.