Machine Learning Fundamentals in R

Actualizat 03.2026

Predict categorical and numeric responses via classification and regression, and discover the hidden structure of datasets with unsupervised learning.

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Machine Learning Fundamentals in R

Learn the basics of prediction using machine learning. This track covers predicting categorical and numeric responses via classification and regression, and discovering the hidden structure of datasets (unsupervised learning). Learn 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.

Cerințe preliminare

Nu există condiții preliminare pentru această pistă

Course
1
Supervised Learning in R: Classification
In this course you will learn the basics of machine learning for classification.
Course
2
Supervised Learning in R: Regression
In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.
Project
Bonus
Predict Future Sales of Fast-Food Menu Items
Help a fast food chain save money and place more accurate orders by building a model to predict food sales.
Course
4
Unsupervised Learning in R
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.
Course
5
Machine Learning with caret in R
This course teaches the big ideas in machine learning like how to build and evaluate predictive models.
Course
6
Modeling with tidymodels in R
Learn to streamline your machine learning workflows with tidymodels.
Course
7
Machine Learning with Tree-Based Models in R
Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.
Skill Assessment
Bonus
Machine Learning Fundamentals in R