Time Series with R Learn the core techniques necessary to extract meaningful insights from time series data. Learn More

Intro to Python for Data Science Master the basics of data analysis in Python. Expand your skill set by learning scientific computing with numpy.

Introduction to R Master the basics of data analysis by manipulating common data structures such as vectors, matrices and data frames.

Intermediate R Continue your journey to become an R ninja by learning about conditional statements, loops, and vector functions.

Importing Data in R (Part 1) In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

Data Manipulation in R with dplyr Master techniques for data manipulation using the select, mutate, filter, arrange, and summarise functions in dplyr.

Writing Functions in R Learn the fundamentals of writing functions in R so you can make your code more readable and automate repetitive tasks.

Introduction to Git for Data Science This course is an introduction to version control with Git for data scientists.

Importing Data in R (Part 2) Parse data in any format. Whether it's flat files, statistical software, databases, or data right from the web.

Reporting with R Markdown Learn to create interactive analyses and automated reports with R Markdown.

Joining Data in R with dplyr This course will show you how to combine data sets with dplyr's two table verbs.

Introduction to Shell for Data Science The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs ...

Data Analysis in R, the data.table Way Master core concepts in data manipulation such as subsetting, updating, indexing and joining your data using data.table.

Introduction to Time Series Analysis Learn the core techniques necessary to extract meaningful insights from time series data.

Forecasting Using R Learn how to make predictions about the future using time series forecasting in R.

String Manipulation in R with stringr Learn how to pull character strings apart, put them back together and use the stringr package.

Manipulating Time Series Data in R with xts & zoo The xts and zoo packages make the task of managing and manipulating ordered observations fast and mistake free.

ARIMA Modeling with R Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

Statistical Modeling in R (Part 1) This course was designed to get you up to speed with the most important and powerful methodologies in statistics.

Foundations of Probability in R In this course, you'll learn about the concepts of random variables, distributions, and conditioning.

Building Dashboards with shinydashboard In this course you'll learn to build dashboards using the shinydashboard package.

Writing Efficient R Code Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

Introduction to Spark in R using sparklyr Learn how to analyze huge datasets using Apache Spark and R using the sparklyr package.

Building Web Applications in R with Shiny: Case Studies Build interactive web apps using R and shiny!

Marketing Analytics in R: Statistical Modeling In this course you'll learn how to use data science for several common marketing tasks.

Data Visualization in R with ggvis Learn to create interactive graphs to display distributions, relationships, model fits, and more using ggvis.

Object-Oriented Programming in R: S3 and R6 Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.

Hierarchical and Mixed Effects Models In this course you will learn to fit hierarchical models with random effects.

Visualizing Time Series Data in R Learn how to visualize time series in R, then practice with a stock-picking case study.

R for SAS, SPSS and STATA Users Learn to translate your knowledge of SAS, SPSS, or Stata into R using the same statistics techniques you're familiar ...

Manipulating Time Series Data in R: Case Studies Strengthen your knowledge of the topics covered in Manipulating Time Series in R using real case study data.

A/B Testing in R Learn A/B testing: including hypothesis testing, experimental design, and confounding variables.

Statistical Modeling in R (Part 2) In this follow-up course, you will expand your stat modeling skills from part 1 and dive into more advanced concepts.

Experimental Design in R In this course you'll learn about basic experimental design, a crucial part of any data analysis.

Working with the RStudio IDE (Part 2) Further your knowledge of RStudio and learn how to integrate Git, LaTeX, and Shiny

Communicating with Data in the Tidyverse Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communica...

Structural Equation Modeling with lavaan in R Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.

Data Visualization in R with lattice Learn to visualize multivariate datasets using lattice graphics.

Data Privacy and Anonymization in R Publicly release data sets with a differential privacy guarantee.

Data Analysis and Statistical Inference This interactive DataCamp course complements the Coursera course Data Analysis and Statistical Inference by Mine Ã‡eti...

How to work with Quandl in R Quandl offers millions of free and open financial, economic, and social datasets. In this tutorial you will learn how...

Intro to Computational Finance with R In this course, you'll make use of R to analyze financial data, estimate statistical models, and construct optimized ...

Big Data Analysis with Revolution R Enterprise Revolution R Enterprise allows R users to process, visualize, and model terabyte-class data sets at a fraction of the...

Intro to Statistics with R: Introduction A friendly introduction to fundamental concepts in statistics in R.

Intro to Statistics with R: Student's T-test If you want to have a solid basic foundation in statistics, it is essential to understand the concepts and theories b...

Intro to Statistics with R: Analysis of Variance (AN... Analysis of Variance (ANOVA) is probably one of the most popular and commonly used statistical procedures. In this co...

Intro to Statistics with R: Repeated measures ANOVA This course focuses on within-groups comparisons and repeated measures design. With the help of a working memory trai...

Intro to Statistics with R: Correlation and Linear R... If you have ever taken a math or statistics class, youâ€™ve probably heard the old adage "Correlation does not imply ca...

Intro to Statistics with R: Multiple Regression Multiple regression is a powerful statistical technique, and here you will discover why and how to use it. Part of th...

Intro to Statistics with R: Moderation and Mediation Moderation and mediation sound alike, but in reality they are quite different. This course will get you acquainted wi...

Kaggle R Tutorial on Machine Learning Always wanted to compete in a Kaggle machine learning competition but not sure you have the right skillset? This inte...

Basic Statistics This course complements course material from the University of Amsterdam's Basic Statistics at Coursera (www.coursera...

Data Exploration With Kaggle Scripts In this course you will begin learning the art and science of data exploration. You'll also become familiar with some...