Data Science

R Programming — Use the R programming language for data analysis, statistical modeling, and data visualization.

R Programming for Data Science: Learn with Practical Exercises

R Programming
Build a strong foundation in data analytics and statistical analysis using R, R Studio, and GGPlot2 through step-by-step, real-world exercises designed for complete beginners.
★ 4.6 (1,681)

Learn R Programming for Data Science and Analytics

R Programming
Master R programming fundamentals, analyze complex datasets, and create clear data visualizations to start your journey in data science and analytics.
★ 4.4 (1,249)

Business Neural Networks in R Studio

R Programming
Master the fundamentals of predictive deep learning and build neural network models for business analysis using R without complex math or coding experience.
★ 4.4 (539)

Decision Trees, Random Forests, and XGBoost in R

R Programming
Learn to build, evaluate, and interpret predictive models using decision trees, ensemble methods, and XGBoost in R to solve practical business problems.
★ 4.3 (243)

Linear and Logistic Regression in R: Regression vs Classification

R Programming
Master the fundamentals of regression and classification in R to solve business problems, prepare data, and interpret predictive models with confidence.
★ 4.7 (374)

R Programming for Beginners: Data Analysis and Visualization

R Programming
Master the fundamentals of R programming to manipulate data, create visualizations, and perform statistical analysis without any prior coding experience.
★ 4.4 (447)

R Programming and Data Analysis with RStudio

R Programming
Learn to import, clean, analyze, and visualize data using RStudio and modern statistical packages.
★ 3.9 (185)

R for Scientific Research: Data Analysis and Visualization

R Programming
Learn to manage datasets, perform statistical tests, and create professional visualizations using R and RStudio for reproducible research.
★ 3.9 (284)

R Programming for Data Science and Statistical Analysis

R Programming
Learn R programming from scratch to perform statistical analysis, clean complex datasets, and build professional data visualizations with ggplot2.
★ 4.5 (5,893)

Intermediate Statistical Analysis in R

R Programming
Learn to perform hypothesis testing, ANOVA, and regression analysis in R using modern data practices to draw meaningful insights from your datasets.
★ 4.3 (392)

Advanced Statistical Modeling in R

R Programming
Learn to perform complex statistical tests, predictive modeling, and data grouping using modern R libraries and tidy data workflows.
★ 4.3 (222)

Machine Learning in R: Theory and Practice of Predictive Modeling

R Programming
Master supervised and unsupervised machine learning algorithms in R, from foundational theory to building predictive models and clustering workflows.
★ 4.5 (239)

Practical Time Series Analysis and Forecasting in R

R Programming
Learn to analyze historical patterns, handle complex date-time formats, and build accurate predictive models in R using both classic and modern tidy frameworks.
★ 4.3 (2,821)

R Programming for Data Science and Statistical Analysis

R Programming
Build a strong foundation in R, from basic data structures to advanced data wrangling and visualization with the Tidyverse.
★ 4.6 (171)

Practical Statistical Modeling and Data Analysis in R

R Programming
Learn how to analyze real-world data, perform hypothesis testing, and build predictive statistical models using modern R programming workflows.
★ 4.4 (2,023)

R Programming for Data Science, Machine Learning, and Shiny Apps

R Programming
Master R programming to analyze complex datasets, build predictive machine learning models, and deploy interactive web applications using Shiny.
★ 4.5 (402)

R Programming for Statistical Analysis

R Programming
Master the fundamentals of R to handle data manipulation, mathematical computations, and statistical modeling with confidence.
★ 4.4 (426)

Practical Time Series Analysis and Forecasting with R

R Programming
Learn to analyze trends, model seasonality, and forecast future values using R through hands-on practical scenarios and real-world datasets.
★ 4.6 (843)

Statistical Simulation in R: Practical Monte Carlo Methods

R Programming
Learn to program probabilistic models and Monte Carlo simulations in R to solve real-world statistical problems with confidence.
★ 4.0 (467)

Data Science and Statistics in R: A Practical Introduction

R Programming
Build a solid foundation in R and statistics by exploring data analysis, visualization, and predictive modeling using real-life scenarios.
★ 3.7 (377)

Practical Data Science in R: Regression, Forecasting, and Text Mining

R Programming
Learn to build regression models, forecast trends, cluster data, and analyze text using R to turn raw datasets into actionable business insights.
★ 4.5 (554)

Regression Analysis in R for Statistics and Machine Learning

R Programming
Build, evaluate, and interpret regression models for statistical analysis and predictive machine learning using R.
★ 4.4 (563)

R Programming for Data Science and Predictive Analytics

R Programming
Build essential skills in data exploration, visualization, and predictive modeling using R and RStudio to solve real-world analytics problems.
★ 4.4 (428)

R Programming for Data Science: Analyze Data and Build Predictive Models

R Programming
Learn to manipulate data, create professional visualizations, and build predictive machine learning models using R and RStudio to solve real-world business problems.
★ 4.1 (255)
Showing 24 of 118 courses