Understanding and Applying t-tests and ANOVAs (jamovi, R)

This workshop will consist of lectures, demonstrations, and exercises in which undergraduate students, graduate students, and faculty will conceptually understand t-tests (e.g., one-sample, independent samples, paired samples) and ANOVAs (e.g., one-way, […]

Spring 2024 Data Science Seminar Series– Milan Sonka

On April 1st, 2024, Dr. Milan Sonka, a Professor for the Department of Electrical and Computer Engineering at the University of Iowa, will present a Data Science seminar on “Interdisciplinary AI Research – Is There a Recipe for Success?”

Understanding and Applying Correlation and Regression (jamovi, R)

This workshop will consist of lectures, demonstrations, and exercises in which undergraduate students, graduate students, and faculty will conceptually understand correlation and regression (e.g., simple, multiple, hierarchical) and apply them […]

AggieSat Laboratory Autonomous Rovers Showcase

AggieSat Laboratory is a student-run space program that trains students in systems engineering through hands-on experience in the design, building, testing, and operation of space systems. Two projects will discuss how their autonomous vehicles will help explore other planets. Join us to see what new adventures await you.

Understanding and Applying Correlation and Regression (jamovi, R)

This workshop will consist of lectures, demonstrations, and exercises in which undergraduate students, graduate students, and faculty will conceptually understand correlation and regression (e.g., simple, multiple, hierarchical) and apply them […]

Applications of AI for Anomaly Detection (NVIDIA DLI Workshop)

Learn how to implement multiple AI-based approaches to solve a specific use case of identifying network intrusions for telecommunications. NVIDIA Course Overview (Do not register through NVIDIA) Instructor: Haoyu Niu, […]

Dive into Reduced Order Modeling with pylibROM

The Digital Twin Lab at Texas A&M Institute of Data Science will host a collaborative workshop on Reduced Order Modeling (ROM), organized in partnership with Texas A&M High Performance Research Computing and the libROM team at Lawrence Livermore National Laboratory (LLNL).