Data, AI, and Cloud Courses

Learn how to structure your PostgreSQL queries to run in a fraction of the time.

This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.

Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.

Use Seaborns sophisticated visualization tools to make beautiful, informative visualizations with ease.

Learn how to work with streaming data using serverless technologies on AWS.

In this course, students will learn to write queries that are both efficient and easy to read and understand.

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

Visualize seasonality, trends and other patterns in your time series data.

Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.

Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.

Using Python and NumPy, learn the most fundamental financial concepts.

Orchestrate data using unions, joins, parsing, and performance optimization in Alteryx.

Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.

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

In this case study, you’ll use visualization techniques to find out what skills are most in-demand for data scientists, data analysts, and data engineers.

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Create more accurate and reliable RAG systems with Graph RAG and hybrid RAG.

Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.

Explore Power BI Service, master the interface, make informed decisions, and maximize the power of your reports.

Explore GDPR through real-world cases on data rights, breaches, and compliance challenges.

Analyze text data in R using the tidy framework.

Advance your Java skills by learning to handle files, process data, and build clean, reusable code using real-world techniques.

Learn how to detect fraud using Python.

Master SQL Server programming by learning to create, update, and execute functions and stored procedures.

Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights.