Data science courses

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

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

Learn how to use GPT tools responsibly and confidently. Discover how these tools work and techniques for writing prompts and evaluating outputs.

Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.

Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.

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

In ecommerce, increasing sales and reducing expenses are top priorities. In this case study, youll investigate data from an online pet supply company.

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

In this course youll learn how to use data science for several common marketing tasks.

Learn the fundamentals of valuing stocks.

Practice your Shiny skills while building some fun Shiny apps for real-life scenarios!

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

Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.

Extract and visualize Twitter data, perform sentiment and network analysis, and map the geolocation of your tweets.

Learn about experimental design, and how to explore your data to ask and answer meaningful questions.

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

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

Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.

Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

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

In this course, youll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.

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

Learn how to make GenAI models truly reflect human values while gaining hands-on experience with advanced LLMs.

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

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

Learn to analyze, plot, and model multivariate data.

Ensure data consistency by learning how to use transactions and handle errors in concurrent environments.

In this course youll learn how to apply machine learning in the HR domain.

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

Learn the bag of words technique for text mining with R.