Data science courses

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

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

Learn how to prepare and organize your data for predictive analytics.

Learn to analyze and model customer choice data in R.

Are you curious about the inner workings of the models that are behind products like Google Translate?

Learn the fundamentals of valuing stocks.

Learn to detect fraud with analytics in R.

Unlock the power of parallel computing in R. Enhance your data analysis skills, speed up computations, and process large datasets effortlessly.

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

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

Learn how to leverage Bayesian estimation methods to make better inferences about linear regression models.

Take your Julia skills to the next level with our intermediate Julia course. Learn about loops, advanced data structures, timing, and more.

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

In this course, you'll learn how to implement more advanced Bayesian models using RJAGS.

Master AWS security, governance, and cost optimization to prepare for the Cloud Practitioner certification.

Learn to build simple models of market response to increase the effectiveness of your marketing plans.

Explore Alteryx Designer in a retail data case study to boost sales analysis and strategic decision-making.

Learn defensive programming in R to make your code more robust.

Learn mixture models: a convenient and formal statistical framework for probabilistic clustering and classification.

Predict employee turnover and design retention strategies.

Learn statistical tests for identifying outliers and how to use sophisticated anomaly scoring algorithms.

Learn how to predict click-through rates on ads and implement basic machine learning models in Python so that you can see how to better optimize your ads.

Master data visualization in Julia. Learn how to make stunning plots while understanding when and how to use them.

Apply fundamental concepts in network analysis to large real-world datasets in 4 different case studies.

Learn to predict labels of nodes in networks using network learning and by extracting descriptive features from the network

Continue learning with purrr to create robust, clean, and easy to maintain iterative code.

Use C++ to dramatically boost the performance of your R code.

You will use Net Revenue Management techniques in Google Sheets for a Fast Moving Consumer Goods company.

Master the essential skills of data manipulation in Julia. Learn how to inspect, transform, group, and visualize DataFrames using real-world datasets.

Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.