Data, AI, and Cloud Courses

Gain the essential skills using Scikit-learn, SHAP, and LIME to test and build transparent, trustworthy, and accountable AI systems.

Master sampling to get more accurate statistics with less data.

Learn the fundamentals of data visualization using Google Sheets.

Find tables, store and manage new tables and views, and write maintainable SQL code to answer business questions.

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

Expand your Google Sheets vocabulary by diving deeper into data types, including numeric data, logical data, and missing data.

Master GitHub Copilot to understand, write, and refine code with context, customization, and smart features.

In this Introduction to DevOps, you’ll master the DevOps basics and learn the key concepts, tools, and techniques to improve productivity.

Conquer NoSQL and supercharge data workflows. Learn Snowflake to work with big data, Postgres JSON for handling document data, and Redis for key-value data.

Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

You will investigate a dataset from a fictitious company called Databel in Tableau, and need to figure out why customers are churning.

Master data manipulation and analysis techniques such as CASE statements, subqueries, and CTEs in Snowflake.

Master the key concepts of data management, from life cycle stages to security and governance.

Discover how Marketing Analysts use data to understand customers and drive business growth.

Learn how to build intelligent agents that reason, act, and solve real-world tasks using Python.

Master data preparation, cleaning, and analysis in Alteryx Designer, whether you are a new or seasoned analyst.

In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.

Explore AI and data monetization strategies, build ethical infrastructures, and align products with business goals.

Discover the exciting world of Deep Learning for Text with PyTorch and unlock new possibilities in natural language processing and text generation.

Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.

This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.

Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control

Learn to use the KNIME Analytics Platform for data access, cleaning, and analysis with a no-code/low-code approach.

In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.

Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.

Learn AI governance with Collibra. Build, embed, and scale responsible AI using tools, frameworks, and MLOps workflows.

Learn how to work with Claude using the Anthropic API to solve real-world tasks and build AI-powered applications.

Learn to create your own Python packages to make your code easier to use and share with others.