Teaching

We offer a range of courses on topics related to business analytics, including "Programming for Data Analytics," "Machine Learning and Artificial Intelligence," "Data Management and Data Visualization," and "Bayesian Data Analytics."

In "Programming for Data Analytics," students will learn the programming basics they need to succeed in data science. This course covers fundamental programming concepts in R, such as data types, control structures, and functions, and shows students how to use these concepts to work with data.

In "Machine Learning and Artificial Intelligence," students will learn about the most important algorithms and techniques used in supervised and unsupervised machine learning. This course covers topics such as regression, classification, clustering, and deep learning, and shows students how to apply these techniques to solve real-world problems.

In "Data Management and Visualization," students will learn about the process of collecting, cleaning, and organizing data, as well as how to visualize data in order to gain insights and communicate findings. This course covers topics such as data warehousing, data integration, and data visualization, and provides hands-on experience working with real-world data sets.

In "Bayesian Data Analytics," students will learn about Bayesian inference, a powerful method for analyzing and making predictions from data. This course covers the basics of Bayesian statistics, including Bayesian estimation, multilevel modeling, and model selection, and shows students how to use Bayesian methods to solve real-world problems.

In addition to these courses, we also offer a Capstone Project in which students work closely with companies to solve real-world analytics challenges. This provides students with the opportunity to apply their knowledge and skills in a real-world setting, and to build their professional network.

If you are interested in learning more about our courses and teaching, we invite you to contact us.