SU5050: Data Mining - Fall 2014 - School of Technology - Michigan Technological University

Instructors

Jessica L. McCarty, PhD (Research Scientist at Michigan Tech Research Institute and Adjunct Assistant Professor at School of Technology) and Michael Billmire, MS (Research Scientist and Software Engineer at MTRI)

Brief Course Description

Overview of current techniques, including theory and applications of data mining and big data for geospatial techniques. Application focuses on open source programming and library development (Python), writing a research plan suitable for research submission, and proof-of-concept study.

The course will be taught in 3 modules via hybrid in-person/online instruction (all lectures/assignments available online). The 14 week semester will be divided across following main topics:


1. Current theory and corporate, engineering, science applications of data mining and big data with a focus
on geospatial applications:

a) What is Big Data?
b) Social media as data source
c) Volunteered Geographic Information
d) GIS and remote sensing data
e) Other databases and database issues
f) Treatment of metadata (spatiotemporal, geolocation, Natural Language Processing)
g) Data mining vs. Data engagement
h) Current practices in corporate data mining: Case study of Google Analytics & Google Earth Engine

2. Lab instruction and development in data mining using open source Python and libraries;

a) Intro Python programming
b) Advancement of programming to intermediate level
c) Databases and database management
d) Treatment of metadata (spatiotemporal, geolocation, Natural Language Processing)
e) Best visualization method and applications

3. Development of a research plan for submission by students as final project, including a proof of concept
study with initial results required and a 5 min overview presentation.

a) Written like an internal grant document, providing students with exposure to sponsored research
technical writing, critical thinking, and online presentation skills.
b) Project development could be used in the enterprise competition, building upon a thesis proposal
and/or project, contribute to internship or practicum credit, or related to current professional goals
and research.

For Additional Information

Jessica McCarty, Ph.D.
Research Scientist
734.994.7236
jmccarty@mtu.edu

Registration information for this online course can be found here:

www.mtu.edu/registrar/students/registration/prepare/