Data science courses

Learn how to use Python parallel programming with Dask to upscale your workflows and efficiently handle big data.

Learn the principles of feature engineering for machine learning models and how to implement them using the R tidymodels framework.

GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science problems.

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

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

Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.

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

Use survival analysis to work with time-to-event data and predict survival time.

Understand the role and real-world realities of Explainable Artificial Intelligence (XAI) with this beginner friendly course.

Explore association rules in market basket analysis with R by analyzing retail data and creating movie recommendations.

Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.

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

Orchestrate data using unions, joins, parsing, and performance optimization in Alteryx.

Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.

Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data.

Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

Learn to solve increasingly complex problems using simulations to generate and analyze data.

Learn how to build an amortization dashboard in Google Sheets with financial and conditional formulas.

Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Python's SimPy package.

Dive into our Tableau case study on supply chain analytics. Tackle shipment, inventory management, and dashboard creation to drive business improvements.

Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.

Learn to rapidly visualize and explore demographic data from the United States Census Bureau using tidyverse tools.

Learn to solve real-world optimization problems using Python's SciPy and PuLP, covering everything from basic to constrained and complex optimization.

This course is for R users who want to get up to speed with Python!

Practice Tableau with our healthcare case study. Analyze data, uncover efficiency insights, and build a dashboard.

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

Learn to use the Bioconductor package limma for differential gene expression analysis.

Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.

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.