Data science courses

Learn to streamline your machine learning workflows with tidymodels.

Master marketing analytics using Tableau. Analyze performance, benchmark metrics, and optimize strategies across channels.

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

Develop the skills you need to clean raw data and transform it into accurate insights.

Level up your GitHub skills with our intermediate course on GitHub Projects, Administration, and advanced security features.

Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.

In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.

Learn how to load, transform, and transcribe speech from raw audio files in Python.

Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling.

Discover how to analyze and visualize baseball data using Power BI. Create scatter plots, tornado charts, and gauges to bring baseball insights alive.

Learn how to visualize time series in R, then practice with a stock-picking case study.

Learn how to design and implement triggers in SQL Server using real-world examples.

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.

Learn how to pull character strings apart, put them back together and use the stringr package.

Learn efficient techniques in pandas to optimize your Python code.

Learn how to build a model to automatically classify items in a school budget.

Learn to process sensitive information with privacy-preserving techniques.

Learn to use the Census API to work with demographic and socioeconomic data.

In this course youll learn how to perform inference using linear models.

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

Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.

Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.