Data, AI, and Cloud Courses

Create visualizations and dynamic dashboards with Databricks, turning raw data into clear and actionable insights.

Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.

In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!

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

Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

Learn to perform linear and logistic regression with multiple explanatory variables.

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.

Learn the fundamentals of AI security to protect systems from threats, align security with business goals, and mitigate key risks.

Learn how to clean data with Apache Spark in Python.

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

Master multi-stage builds, Docker networking tools, and Docker Compose for optimal containerized applications!

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

Get your AI Act together! Understand the obligations, risks, and requirements of the EU AI Act.

Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.

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

Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

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

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

Explore Azure services like Compute, Storage, and Automation, with hands-on experience.

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

Take your reporting skills to the next level with Tableau’s built-in statistical functions.

Build the foundation you need to think statistically and to speak the language of your data.

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.

Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.

Learn and use powerful Deep Reinforcement Learning algorithms, including refinement and optimization techniques.

Learn to bring data into Microsoft Fabric, covering Pipelines, Dataflows, Shortcuts, Semantic Models, security, and model refresh.

Prepare for your next coding interviews in Python.

Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!

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 build interactive and insight-rich dashboards with Dash and Plotly.