Data, AI, and Cloud Courses

This introductory and conceptual course will help you understand the fundamentals of data warehousing.

Take your Power BI visualizations up a level with the skills you already have. Learn alternative data storytelling techniques to simply building dashboards.

Learn how to use GitHubs various features, navigate the interface and perform everyday collaborative tasks.

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.

Bring your Google Sheets to life by mastering fundamental skills such as formulas, operations, and cell references.

Explore data structures such as linked lists, stacks, queues, hash tables, and graphs; and search and sort algorithms!

The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs on clusters and clouds.

Apply your skills to import, analyze and visualize Human Resources (HR) data using Power BI.

Learn the architecture behind GPT models and master advanced prompt crafting to unlock ChatGPTs full potential.

Learn to write efficient code that executes quickly and allocates resources skillfully to avoid unnecessary overhead.

In this course, youll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.

Discover how MLOps can take machine learning models from local notebooks to functioning models in production that generate real business value.

Improve data literacy skills by analyzing remote working policies.

Learn the nuts and bolts of LLMs and the revolutionary transformer architecture they are based on!

Learn to build effective, performant, and reliable data pipelines using Extract, Transform, and Load principles.

Discover the different ways you can enhance your Power BI data importing skills.

Master your skills in NumPy by learning how to create, sort, filter, and update arrays using NYC’s tree census.

Enhance your reports with trend analysis techniques such as time series, decomposition trees, and key influencers.

Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.

Explore Excel Power Query for advanced data transformation and cleansing to boost your decision-making and analysis.

Learn how to implement and schedule data engineering workflows.

Learn about the power of Microsoft Azure and cloud computing software to help you improve your data engineering skills.

Continue your data visualization journey where youll learn practical techniques for incorporating DAX measures and progressive disclosure in your reports.

Master Responsible AI Practices with this comprehensive course, featuring real-world case studies and interactive content.

Discover what it takes to scale AI agents, with a little help from frameworks like MCP and A2A.

Learn how to deploy and maintain assets in Power BI. You’ll get to grips with the Power BI Service interface and key elements in it like workspaces.

Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

This course introduces dbt for data modeling, transformations, testing, and building documentation.

Leverage the OpenAI API to get your AI applications ready for production.