2023_02_03-Engineering - Toor Lab jatorner -0112.JPG
Big data/data mining concerns the analyses of enormous data sets and the extraction of meaning or useful information from them using computer algorithms and/or software tools. Data mining can be used to predict behavior and future trends allowing business to make knowledge-driven decisions.
Big data/data mining tasks include data summarization, clustering, classification, prediction, and dependency analysis. Big data/data mining relies heavily on algorithms and statistical methods to uncover patterns and create models of the data.
This area can benefit a broad spectrum of industries helping them to increase profits by reducing costs and/or raising revenue. Students pursuing this FA could literally work in any organization that stores data and is interested in putting that data to good use.
Students interested in this FA are encouraged to consider the course suggestions listed below when completing their plan of study form.
| Computer Science and Engineering Requirements | Courses |
|---|---|
| Theory Elective (Select one) | ECE:5200 Machine Learning (Same as: IGPI:5450) CS:5430 Machine Learning |
| 5000-Level ECE Elective (Select one) | ECE:5225 Statistical Foundations of Inference and Machine Learning ECE:5250 Large Language Models ECE:5320 High Performance Computer Architecture (Same as: CS:5610) ECE:5330 Graph Algorithms and Combinatorial Optimization (Same as: IGPI:5331) ECE:5485 Intelligent Vision and Image Understanding ECE:5550 Internet of Things ECE:5840 Software Security |
| 4000-level or above CS Elective (Select one) | CS:4400 Database Systems CS:4420 Artificial Intelligence CS:4440 Web Mining CS:4980 Topics in Computer Science II (VARIES BY SEMESTER - Not all sections may be acceptable) CS:4720 Optimization Techniques (Same as: MATH:4820) |
| ECE Elective (Select one) | All 5000-level ECE electives listed above, and ENGR:3110 Intro to AI & Machine Learning in Engr |
| CS Elective (Select one) | All 4000-level and above CS electives listed above, and CS:3700 Elementary Numerical Analysis (Same as: MATH:3800) |
| Additional Electives (Select two 3 s.h.) | Any of the below OR course selected in consultation with advisor. MATH:4040 Matrix Theory |
Advising Notes
- If you have special interest in a particular data mining domain it is recommend that you also take one or two courses that provide background in that domain. Introductory courses in bioinformatics, business, or marketing are examples of domains where data mining is often applied.
- A minor in mathematics can be earned by including two qualifying math courses in the FA plan.