Learn how to efficiently collect and download data from any website using R.

Learn to build recommendation engines in Python using machine learning techniques.

Leverage the tools in the tidyverse to generate, explore and evaluate machine learning models.

Learn how to deploy and maintain assets in Power BI. You’ll get to grips with the Power BI Service interface and key elements in it like workspaces.

Explore latent variables, such as personality using exploratory and confirmatory factor analyses.

This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.

Learn how to perform advanced dplyr transformations and incorporate dplyr and ggplot2 code in functions.

Visualize seasonality, trends and other patterns in your time series data.

Learn to easily summarize and manipulate lists using the purrr package.

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.

Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.

Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.

In this course you'll learn how to create static and interactive dashboards using flexdashboard and shiny.

Analyze time series graphs, use bipartite graphs, and gain the skills to tackle advanced problems in network analytics.