Data, AI, and Cloud Courses

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

Combine text, images, audio, and video with the latest AI models from Hugging Face, and generate new images and videos!

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

Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.

Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!

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

Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.

Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

Learn how to load, transform, and transcribe speech from raw audio files in Python.

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

Unlock the power of parallel computing in R. Enhance your data analysis skills, speed up computations, and process large datasets effortlessly.

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

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

Learn to build pipelines that stand the test of time.

Learn the principles of feature engineering for machine learning models and how to implement them using the R tidymodels framework.

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

In this course youll learn how to leverage statistical techniques for working with categorical data.

Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.

Dive into our Tableau case study on supply chain analytics. Tackle shipment, inventory management, and dashboard creation to drive business improvements.

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

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

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

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

Learn efficient techniques in pandas to optimize your Python code.

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

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

Learn to use Amazon Bedrock to access foundation AI models and build with AI - without managing complex infrastructure.

Learn how to access financial data from local files as well as from internet sources.

Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.