Introduction to Time Series Analysis Learn the core techniques necessary to extract meaningful insights from time series data. 4 hours Play preview

Statistical Thinking in Python (Part 1) Build the foundation you need to think statistically and to speak the language of your data. 3 hours Play preview

Statistical Thinking in Python (Part 2) Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing. 4 hours Play preview

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. 4 hours

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. 4 hours

Foundations of Inference Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference. 4 hours Play preview

Exploratory Data Analysis Learn how to use graphical and numerical techniques to begin uncovering the structure of your data. 4 hours Play preview

Correlation and Regression Learn how to describe relationships between two numerical quantities and characterize these relationships graphically. 4 hours Play preview

Introduction to Data Learn the language of data, study types, sampling strategies, and experimental design. 4 hours Play preview

ARIMA Modeling with R Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R. 4 hours Play preview

Network Analysis in Python (Part 1) This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library. 4 hours Play preview

Sentiment Analysis in R Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelli... 4 hours

Foundations of Probability in R In this course, you'll learn about the concepts of random variables, distributions, and conditioning. 4 hours Play preview

Forecasting Using R Learn how to make predictions about the future using time series forecasting in R. 5 hours Play preview

Spatial Statistics in R Learn how to make sense of spatial data and deal with various classes of statistical problems associated with it. 4 hours Play preview

Sentiment Analysis in R: The Tidy Way In this course, you will the learn principles of sentiment analysis from a tidy data perspective. 4 hours Play preview

Network Analysis in Python (Part 2) Analyze time series graphs, use bipartite graphs, and gain the skills to tackle advanced problems in network analytics. 4 hours Play preview

Multiple and Logistic Regression In this course you'll lear to add multiple variables to linear models and to use logistic regression for classification. 4 hours Play preview

Inference for Linear Regression In this course you'll learn how to perform inference using linear models. 4 hours

Introduction to Time Series Analysis in Python In this course you'll learn the basics of analyzing time series data. 4 hours Play preview

Spatial Analysis in R with sf and raster Analyze spatial data using the sf and raster packages. 4 hours Play preview

Network Analysis in R In this course you'll learn to analyze and visualize network data with the igraph package. 4 hours Play preview

Case Studies in Statistical Thinking Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract ac... 4 hours Play preview

Inference for Numerical Data In this course you'll learn techniques for performing statistical inference on numerical data. 4 hours

Fundamentals of Bayesian Data Analysis in R Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox. 4 hours

Inference for Categorical Data In this course you'll learn how to leverage statistical techniques for working with categorical data. 4 hours

Business Process Analytics in R Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data. 4 hours

Forecasting Product Demand in R Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of pr... 4 hours Play preview

Marketing Analytics in R: Statistical Modeling In this course you'll learn how to use data science for several common marketing tasks. 4 hours Play preview

Network Analysis in R: Case Studies Apply fundamental concepts in network analysis to large real-world datasets in 4 different case studies. 4 hours

Hierarchical and Mixed Effects Models In this course you will learn to fit hierarchical models with random effects. 4 hours Play preview

Customer Analytics & A/B Testing in Python Learn how to use Python to create, run, and analyze A/B tests to make proactive business decisions. 4 hours

Nonlinear Modeling in R with GAMs GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science ... 4 hours

Bayesian Modeling with RJAGS In this course, you'll learn how to implement more advanced Bayesian models using RJAGS. 4 hours

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. 4 hours Play preview

Factor Analysis in R Explore latent variables, such as personality using exploratory and confirmatory factor analyses. 4 hours

Marketing Analytics in R: Choice Modeling Learn to analyze and model customer choice data in R. 4 hours

Experimental Design in R In this course you'll learn about basic experimental design, a crucial part of any data analysis. 4 hours Play preview

Bayesian Regression Modeling with rstanarm Learn how to leverage Bayesian estimation methods to make better inferences about linear regression models. 4 hours

Analyzing Survey Data in R Learn survey design using common design structures followed by visualizing and analyzing survey results. 4 hours Play preview

Mixture Models in R Learn mixture models: a convenient and formal statistical framework for probabilistic clustering and classification. 4 hours

A/B Testing in R Learn A/B testing: including hypothesis testing, experimental design, and confounding variables. 4 hours

Statistical Simulation in Python Learn to solve increasingly complex problems using simulations to generate and analyze data. 4 hours

Predictive Analytics using Networked Data in R Learn to predict labels of nodes in networks using network learning and by extracting descriptive features from the n... 4 hours

Generalized Linear Models in R The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression. 4 hours