Data, AI, and Cloud Courses

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

Advance you R finance skills to backtest, analyze, and optimize financial portfolios.

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

Master AI for marketing to plan smarter campaigns, create quality content, and build custom AI agents.

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

Advance your Alteryx skills with real fitness data to develop targeted marketing strategies and innovative products!

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.

Strengthen your knowledge of the topics covered in Manipulating Time Series in R using real case study data.

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

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

In this course, youll learn how to implement more advanced Bayesian models using RJAGS.

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

Learn to create animated graphics and linked views entirely in R with plotly.

Learn to detect fraud with analytics in R.

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

Learn how to visualize big data in R using ggplot2 and trelliscopejs.

Manipulate text data, analyze it and more by mastering regular expressions and string distances in R.

This course will show you how to combine and merge datasets with data.table.

Learn to analyze and model customer choice data in R.

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

Predict employee turnover and design retention strategies.

Learn how to tune your models hyperparameters to get the best predictive results.

Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.

Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of products from a real world example.

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

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

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

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

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

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