IA 340: Data Mining, Modeling, and Knowledge Discovery in Databases
IA 340: Data Mining, Modeling, and Knowledge Discovery in Databases
An introduction to modern Data Analytics, Cloud Databases, and AI integration for Intelligence Analysis.
đź“– Course Syllabus
Review the Fall 2026 course policies, grading structure, and official AI guidelines.
🚀 Module 1
Intro to Data Mining & Workspace Onboarding
đź“ť Week 1 Assignment
Account Setup & AI Program Registration
Course Overview
IA 340 provides a comprehensive introduction to modern data analysis, teaching students how to collect, organize, query, and quantitatively analyze data. Moving beyond basic spreadsheets, this course introduces the tools and techniques used in modern cloud and AI-assisted environments.
Course Roadmap / Major Modules
- Workspace & Foundations: Google Colab, Python, and generative AI integration.
- Relational Data: Relational database workflows and structural querying.
- NoSQL & Social Data: Document databases, unstructured data, and social media analysis.
- AI-Assisted Analysis: Vector embeddings, AI-assisted data mining, and applied insights.
- Final Project: End-to-end data collection, modeling, and discovery.
Official Course Information
See the official JMU Intelligence Analysis Undergraduate Curriculum and the current university catalog for official IA 340 prerequisites and course descriptions.
Instructor
Dr. Xuebin Wei
Associate Professor, James Madison University (Geography / Intelligence Analysis)
Email: weixx@jmu.edu
Official JMU Faculty Profile
Repository / Reuse / Privacy Boundary
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