Data, AI, and Cloud Courses

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

Learn data management in Databricks with Delta Lake, including ACID transactions, schema enforcement, and security.

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

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

Learn to easily summarize and manipulate lists using the purrr package.

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

Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.

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

Automate data manipulation with KNIME, mastering merging, aggregation, database workflows, and advanced file handling.

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

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

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

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

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

Analyze time series graphs, use bipartite graphs, and gain the skills to tackle advanced problems in network analytics.

Learn how to build an amortization dashboard in Google Sheets with financial and conditional formulas.

Learn how to effectively and efficiently join datasets in tabular format using the Python Pandas library.

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

Learn to analyze and model customer choice data in R.

This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.

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

Learn how computers work, design efficient algorithms, and explore computational theory to solve real-world problems.

Learn to process sensitive information with privacy-preserving techniques.

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

Learn to create compelling data visualizations with KNIME, covering charts, components, and dashboards.

Learn to analyze, plot, and model multivariate data.

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

Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

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

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