Statistics & Probability Courses and Certifications

Introduction to Statistical Modeling in R

This course is designed to get you up to speed with the most important and powerful methodologies in statistics.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Descriptive Statistics

2 ratings at Udacity

Learn to summarize data using data types, measures of center and spread, distribution shape, and outliers.

• Udacity
• 9 hours
• Self-Paced
• Paid Course

Linear and Logistic Regression

1 rating at Udacity

Learn to fit and interpret simple and multiple linear regression models, then apply logistic regression to classification problems in Python.

• Udacity
• 20 hours
• Self-Paced
• Paid Course

Spatial Statistics in R

Learn how to make sense of spatial data and deal with various classes of statistical problems associated with it.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Intermediate Statistical Modeling in R

In this follow-up course, you will expand your stat modeling skills from the introduction and dive into more advanced concepts.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Statistical Inference in R

Familiarize yourself with the core set of skills in statistical inference necessary to understand, interpret, and tune your statistical & machine learning models.

• DataCamp
• 16 hours
• Self-Paced
• Free Trial Available

Performing Experiments in Python

Learn about experimental design, and how to explore your data to ask and answer meaningful questions.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Probability

Build foundational probability skills—from coins and dice to binomial distributions, conditional probability, and Bayes’ Rule—then apply them to basketball shooting data.

• Udacity
• 13 hours
• Self-Paced
• Paid Course

Causal Inference

Learn to estimate and validate causal effects from observational time-series and panel data using advanced causal inference methods.

• Udacity
• 13 hours
• Self-Paced
• Paid Course

Hypothesis Testing

Learn to use statistical inference, confidence intervals, hypothesis testing, and A/B tests to evaluate experiments with Python.

• Udacity
• 21 hours
• Self-Paced
• Paid Course

Career Certificate

Applied Statistics

Move beyond prediction to evidence-backed business decisions: forecast revenue, estimate causal effects, model customer choice, and stress-test recommendations with Bayesian decision tools.

• Udacity
• 60 hours
• Self-Paced
• Paid Course

Mode

Statistics for Data Science

Learn the statistical concepts and techniques you need to conduct rigorous inferential analysis and draw accurate conclusions from data sets.

• Udacity
• 4 weeks
• Self-Paced
• Free Online Course

Career Certificate

Data Analytics Foundations Course Online (Self-Paced)

Build a data analytics foundation by connecting statistical analysis, forecasting, visualization, and optimization to strategic decision-making.

• Noble Desktop
• Self-Paced
• $595.00

A look at using Instrumental Variables and Regression Discontinuity to estimate causal effects

• DataCamp
• Self-Paced
• Free Trial Available

Welcome to the 3rd course in our series on causal inference concepts and methods created by Duke University with support from eBay, Inc.

• DataCamp
• Self-Paced
• Free Trial Available