Data, AI, and Cloud Courses

Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.

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

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

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

Elevate your analysis with this hands-on course using SQL with DataLab workbooks.

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

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

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

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

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

Learn to detect fraud with analytics in R.

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

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

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

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.

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

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

Learn to analyze and model customer choice data in R.

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

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

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

Predict employee turnover and design retention strategies.

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.

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

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 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.

Apply AI in finance to analyze data, prompt effectively, and automate workflows for better decisions.