Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.

Sharpen your knowledge in machine learning, and prepare for any potential question you might get in a machine learning interview in Python.

Learn to streamline your machine learning workflows with tidymodels.

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

Learn to analyze, plot, and model multivariate data.

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

Advance you R finance skills to backtest, analyze, and optimize financial portfolios.

Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.

Discover the different ways you can enhance your Power BI data importing skills.

Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

Learn how to make attractive visualizations of geospatial data in Python using the geopandas package and folium maps.

In this course you'll learn to analyze and visualize network data with the igraph package.

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

Learn how to create interactive data visualizations, including building and connecting widgets using Bokeh!

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.