Data, AI, and Cloud Courses

Enhance your KNIME skills with our course on data transformation, column operations, and workflow optimization.

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

Learn how to efficiently collect and download data from any website using R.

Discover how to talk to your data using text-to-query AI agents with MongoDB and LangGraph.

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

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

Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.

Learn to streamline your machine learning workflows with tidymodels.

Learn to create, secure, and manage APIs with Azure API Management through hands-on practice.

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

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

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

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

Learn how to use Python parallel programming with Dask to upscale your workflows and efficiently handle big data.

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

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

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

Learn how to pull character strings apart, put them back together and use the stringr package.

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

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 to solve increasingly complex problems using simulations to generate and analyze data.

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

Learn the bag of words technique for text mining with R.

Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

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

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.

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