Data, AI, and Cloud Courses

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

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

Learn to create interactive dashboards with R using the powerful shinydashboard package. Create dynamic and engaging visualizations for your audience.

Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.

Test a chatbot that matches customers with ideal skincare products using your prompting skills for personalized results.

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

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

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

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

Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.

Learn to work with Plain Old Java Objects, master the Collections Framework, and handle exceptions like a pro, with logging to back it all up!

In this course youll learn techniques for performing statistical inference on numerical data.

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

This course is for R users who want to get up to speed with Python!

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

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

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 efficient techniques in pandas to optimize your Python code.

Learn to build pipelines that stand the test of time.

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.

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

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

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

Practice your Shiny skills while building some fun Shiny apps for real-life scenarios!

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

Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.

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

Explore HR data analysis in Tableau with this case study.