Data Science in R: Regression & Classification Analysis

Regression Analysis and Classification for Machine Learning & Data Science in R

My course will be your hands–on guide to the theory and applications of supervised machine learning with a focus on regression analysis and classification using the R–programming language.

Unlike other courses, it offers NOT ONLY the guided demonstrations of the R–scripts but also covers theoretical background that will allow you to apply and understand REGRESSION ANALYSIS and CLASSIFICATION (Linear Regression, Random Forest, KNN, etc) in R. We will cover many R packages incl. caret package for supervised machine learning tasks.

This course also covers all the main aspects of practical and highly applied data science related to Machine Learning (i.e. regression analysis). Thus, if you take this course, you will save lots of time & money on other expensive materials in the R based Data Science and Machine Learning domain.

THIS COURSE HAS 8 SECTIONS COVERING EVERY ASPECT OF MACHINE LEARNING: BOTH THEORY & PRACTISE

Fully understand the basics of supervised Machine Learning for Regression Analysis and classification tasks

Harness applications of parametric and non–parametric regressions & classification methods in R

Learn how to apply correctly regression & classification models and test them in R

Learn how to select the best machine learning model for your task