R Datacamp Courses

R Programming

  • Introduction to R
  • Intermediate R
  • Object-Oriented Programming with S3 and R6 in R
  • String Manipulation with stringr in R
  • Parallel Programming in R
  • Intermediate R: Practice
  • Data Manipulation with data.table in R
  • Writing Efficient R Code
  • Introduction to the Tidyverse

R Importing and Cleaning Data

  • Introduction to Importing Data in R
  • Cleaning Data in R
  • Intermediate Importing Data in R
  • Working with Web Data in R

Data Manipulation in R

  • Working with Data in the Tidyverse
  • Manipulating Time Series Data with xts and zoo in R
  • Introduction to Text Analysis in R
  • Joining Data with data.table in R
  • Categorical Data in the Tidyverse

Data Visualization in R

  • Data Visualization with lattice in R
  • Data Visualization with ggplot2 (Part 1-2-3)
  • Visualization Best Practices in R
  • Communicating with Data in the Tidyverse
  • Data Visualization in R

Probability and Statistics

  • Introduction to Data in R
  • Correlation and Regression in R
  • Exploratory Data Analysis in R
  • Time Series Analysis in R
  • Multiple and Logistic Regression in R
  • Forecasting in R
  • Modeling with Data in the Tidyverse
  • Foundations of Probability in R
  • Linear Algebra for Data Science in R
  • Foundations of Inference in R
  • ARIMA Modeling with R
  • Statistical Modeling in R (Part 1 & 2)
  • Experimental Design in R
  • A/B Testing in R
  • Inference for Categorical Data in R
  • Generalized Linear Models in R
  • Network Analysis in R
  • Inference for Linear Regression in R
  • Factor Analysis in R
  • Forecasting Product Demand in R
  • Anomaly Detection in R
  • Inference for Numerical Data in R
  • Choice Modeling for Marketing in R
  • Multivariate Probability Distribution in R
  • Building Response Models in R
  • Predictive Analytics using Networked Data in R
  • Mixture Models in R
  • Probability Puzzles in R

Machine Learning in R

  • Supervised Learning in R : Classification
  • Introduction to Machine Learning
  • Cluster Analysis in R
  • Unsupervised Learning in R
  • Machine Learning Toolbox
  • Supervised Learning in R : Regression
  • Machine Learning with Tree Based Models in R
  • Text Mining: Bag of Words
  • Sentiment Analysis in R
  • Machine Learning for Marketing Analytics in R
  • Advanced Dimensionality Reduction in R
  • Dimensionality Reduction in R
  • Sentiment Analysis in R: Tidy Way
  • Fraud Detection in R
  • Feature Engineering in R

Applied Finance

  • Introduction to R for Finance
  • Credit Risk Modeling in R
  • Intermediate R for Finance
  • Introduction to Portfolio Analysis in R
  • Importing and Managing Financial Data in R
  • Financial Trading in R
  • Bond Valuation and Analysis in R
  • Quantitative Risk Management in R
  • Financial Analytics in R
  • Intermediate Portfolio Analytics
  • GARCH Models in R
  • Equity Valuation in R
  • Life Insurance Products Valuation in R