Datacamp

Take your reporting skills to the next level with Tableau’s built-in statistical functions. Using drag and drop analytics, you'll learn how to perform univariate and bivariate exploratory data analysis and create regression models to spot...

Probability is the study of regularities that emerge in the outcomes of random experiments. In this course, you'll learn about fundamental probability concepts like random variables (starting with the classic coin flip example) and how...

The tidyverse includes a tremendous set of packages that make working with data simple and fast. But have you ever tried to put dplyr functions inside functions and been stuck with strange errors or unexpected...

Managing risk using Quantitative Risk Management is a vital task across the banking, insurance, and asset management industries. It’s essential that financial risk analysts, regulators, and actuaries can quantitatively balance rewards against their...

A good proportion of the data out there in the real world is inherently spatial. From the population recorded in the national census, to every shop in your neighborhood, the majority of datasets have a...

After learning the basics of using Shiny to build web applications, this course takes you to the next level by putting your newly acquired skills into practice. You'll get experience developing fun and realistic Shiny...

You have experience working with databases or, perhaps, you have heard how useful databases can be for organizing your data. Have you ever wanted to create and manage your own databases but thought such knowledge...

Are you looking to land that next job or hone your statistics interview skills to stay sharp? Get ready to master classic interview concepts ranging from conditional probabilities to A/B testing to the bias-variance tradeoff,...

Do patients taking the new drug survive longer than others? How fast do people get a new job after getting unemployed? What can I do to make my friends stay on the dancefloor at my...

In this course, you will learn the foundations of A/B testing, including hypothesis testing, experimental design, and confounding variables. You will also be exposed to a couple more advanced topics, sequential analysis and multivariate testing....

They say that a picture is worth a thousand words. Indeed, successfully promoting your data analysis is not only a matter of accurate and effective graphics, but also of aesthetics and uniqueness. This course teaches...

Did you know that data scientists and data analysts spend a large amount of time cleaning data before they can analyze it? This is because real-world data is messy. To help you navigate messy data...

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

You've taken a survey (or 1000) before, right? Have you ever wondered what goes into designing a survey and how survey responses are turned into actionable insights? Of course you have! In Analyzing Survey Data...

Mastery requires practice. Having completed Statistical Thinking I and II, you developed your probabilistic mindset and the hacker stats skills to extract actionable insights from your data. Your foundation is in place, and now it...

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

In Financial Forecasting in Python, you will step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast, the basics of income statements...

Bayesian data analysis is an increasingly popular method of statistical inference, used to determine conditional probability without having to rely on fixed constants such as confidence levels or p-values. In this course, you’ll learn how...

In Quantitative Risk Management (QRM), you will build models to understand the risks of financial portfolios. This is a vital task across the banking, insurance and asset management industries. The first step in the model...

When working with big data, you’ll face two common obstacles: using too much memory and long runtimes. The Dask library can lower your memory use by loading chunks of data only when needed. It can...