Data, AI, and Cloud Courses

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

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

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.

Explore a range of programming paradigms, including imperative and declarative, procedural, functional, and object-oriented programming.

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

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

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

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

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

Master AI for marketing to plan smarter campaigns, create quality content, and build custom AI agents.

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

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

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

Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data.

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

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

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

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

Learn to streamline your machine learning workflows with tidymodels.

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

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

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

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

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

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.

Explore GDPR through real-world cases on data rights, breaches, and compliance challenges.

In ecommerce, increasing sales and reducing expenses are top priorities. In this case study, youll investigate data from an online pet supply company.

Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.

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