Data, AI, and Cloud Courses

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

Learn essential finance math skills with practical Excel exercises and real-world examples.

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

Build SQL skills by writing AI prompts that generate queries for sorting, grouping, filtering, and categorizing data.

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

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

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!

In this course, youll learn how to import and manage financial data in Python using various tools and sources.

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

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

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

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.

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.

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

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

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

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

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

Learn how to detect fraud using Python.

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

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

Explore ways to work with date and time data in SQL Server for time series analysis

Analyze text data in R using the tidy framework.

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

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

Learn to manipulate and analyze flexibly structured data with MongoDB.

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

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

Learn the core techniques necessary to extract meaningful insights from time series data.

Solidify your decision science skills by designing data-informed frameworks and implementing efficient solutions.