|
IT Concentration: Machine and Computational Learning
For those entering the program Fall 2003 semester & beyond
Contacts: Mark Goldberg and Malik Magdon-Ismail
Description:
This concentration of study prepares a student to work in the areas of Information Technology that involve the development of intelligent systems for complex computational tasks in areas such as bioinformatics, voice and image recognition, and Internet development.
The knowledge of the methods of machine and computational learning enables the student not only to identify situations where intelligent algorithms would amplify performance, but also to develop such algorithms.
| Semester I |
Semester II |
|
ITEC-1210 Information in History & Society
CSCI-1100 Computer Science I
MATH-1010 Calculus I
Science Elective
|
ITEC-1220 Politics & Economics of IT
CSCI-1200 Computer Science II
MATH-1020 Calculus II (Math Elective)
Science Elective
|
| Semester III |
Semester IV |
| CSCI-2300 Data Structures & Algorithms
ITEC-2210 Intro to Human Computer Interaction
ITEC-2110 Exploiting the Information World
H&SS Elective**
|
CSCI-2500 Computer Organization
Machine Learning Elective
ITEC-2960 Creative Design in IT
Free Elective
|
| Semester V |
Semester VI |
IT Elective (one of):
- CSCI-4380 Database Systems
- DSES-4530 Information Systems
DSES-4750 Probability Theory & Applications
Machine Learning Elective
H&SS Elective**
|
CSCI-4150 Intro to Artificial Intelligence
ITEC-4310 Managing IT Resources
H&SS Elective**
Machine Learning Elective
|
| Semester VII |
Semester VIII |
|
ITEC-4100 IT Capstone Experience
Machine Learning Elective
Machine Learning Elective
Free Elective
|
CSCI-4960 Computational/Machine Learning
Machine Learning Seminar/Project
H&SS Elective**
Free Elective
|
Machine Learning Electives may be chosen from among: CSCI-4999 Machine Learning in Bioinformatics, CSCI-4020 Computer Algorithms, CSCI-4963 Data Mining, PHIL-2140 Introduction to Logic, PHIL-4260 Philosophy of Artificial Intelligence, and DSES-4810 Computational Intelligence. The following graduate courses can be used as Machine Learning Electives with the permission of either Prof. Goldberg or Prof. Magdon-Ismail: CSCI-6150 AI and Heuristics, ECSE-6610 Pattern Recognition, ECSE-6720 Neural Network Computing, and ECSE-6760 AI.
**See H&SS requirements
|
