Enroll in CSCE 386: Data Science Seminar

Enroll in CSCE 386: Data Science Seminar.
Enroll in CSCE 386: Data Science Seminar.

CSCE 386: Data Science Seminar
Practice and Professional Development – Fall 2025
Tue/Thu 11:00 AM–12:15 PM
Kiewit Hall A445
Instructor: Dr. Juan Cui (jcui@unl.edu)

About the Course
Curious about how data science powers discoveries and decisions? This seminar series brings together faculty experts, industry leaders, and government professionals to share real-world insights into data science applications. Over the semester, a total of 26 invited talks are scheduled, offering students exposure to a diverse set of perspectives and practices.

Students will explore how data is collected, managed, analyzed, and applied to solve pressing challenges in biomedicine, economics, energy, geospatial analytics, governance, and AI innovation.

What You’ll Gain
• Broad exposure to cutting-edge research, innovative industry practices, and government applications.
• Hands-on experience through reflections, peer discussions, and group projects.
• Opportunities to learn directly from leaders at UNL, City of Lincoln, USDA, Amazon Web Services, Sandhills Global, LES, and more.
• A chance to build teamwork, communication, and professional development skills.

Sample Seminar Topics
• Data Analysis and Modeling in Biomedical Research
• Data & Economic Inequality
• Power Trading and Risk Analytics
• Big Data in the Cloud with GIS
• AI for Text, Image, and Recommendation Systems
• Crime Data Analytics and Public Safety
• Modeling Demand in Forestry & Energy
• Topological Data Analysis for Multi-Modal Data Fusion
• Geodata: Without It You’re Lost

How You’ll Be Evaluated
• Reflection Essays (30%) – Capture insights from talks
• Group Project Proposal (30%) – Develop a real-world data-driven solution
• Peer Review & Discussions (20%) – Engage in collaborative critique and dialogue
• Group Presentation (20%) – Present and defend your proposal

Join us this fall and discover how data science transforms ideas into impact — across research, industry, and government.