Data, AI, and Cloud Courses

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

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

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

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

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

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

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

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.

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

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

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

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

Learn to detect fraud with analytics in R.

Learn to analyze and model customer choice data in R.

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

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.

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

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

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.

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

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

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

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