Data, AI, and Cloud Courses

Automate data manipulation with KNIME, mastering merging, aggregation, database workflows, and advanced file handling.

Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.

Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

Learn to set up a secure, efficient book recommendation app in Azure in this hands-on case study.

Learn to create compelling data visualizations with KNIME, covering charts, components, and dashboards.

Learn to use the Bioconductor package limma for differential gene expression analysis.

Apply financial analysis in KNIME with real-world data, enhancing data preparation and workflow skills.

Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

Discover what all of the DeepSeek hype was really about! Build applications using DeepSeeks R1 and V3 models.

Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling.

Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.

Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.

Use survival analysis to work with time-to-event data and predict survival time.

Learn how to visualize time series in R, then practice with a stock-picking case study.

Learn to use the Census API to work with demographic and socioeconomic data.

This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.

Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.

Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

Practice Tableau with our healthcare case study. Analyze data, uncover efficiency insights, and build a dashboard.

Learn to streamline your machine learning workflows with tidymodels.

Master data cleaning in Java using statistical methods, transformations, and validation for reliable apps.

Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.

Ensure data consistency by learning how to use transactions and handle errors in concurrent environments.

Learn how to perform advanced dplyr transformations and incorporate dplyr and ggplot2 code in functions.

Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Pythons SimPy package.

Learn how to design, automate, and monitor scalable forecasting pipelines in Python.