Data, AI, and Cloud Courses

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

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

Learn how to clean data with Apache Spark in Python.

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

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

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

Master strategic data management for business excellence.

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

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

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

Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.

Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

Learn how computers work, design efficient algorithms, and explore computational theory to solve real-world problems.

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

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

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

Learn the theory behind responsibly managing your data for any AI project, from start to finish and beyond.

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

Learn about ARIMA models in Python and become an expert in time series analysis.

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

Learn how to build interactive and insight-rich dashboards with Dash and Plotly.

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

Sharpen your skills in Oracle SQL including SQL basics, aggregating, combining, and customizing data.

Prepare for your next coding interviews in Python.

Discover how the Pinecone vector database is revolutionizing AI application development!

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

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

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

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