|
IT Concentration: Machine and Computational Learning
For those entering the program Fall 2004 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-2110 Exploiting the Information World
ITEC-2960 Creativity and IT
H&SS Elective**
|
CSCI-2500 Computer Organization
Machine Learning Elective (see below)
ITEC-2210 Intro to Human Computer Interaction
Free Elective
|
| Semester V |
Semester VI |
IT Elective (one of):
- CSCI-4380 Database Systems
- MGMT-496X Data Resource Management
DSES-4750 Probability Theory & Applications
ITEC-4310 Managing IT Resources
Machine Learning Elective
|
CSCI-4150 Intro to Artificial Intelligence
Machine Learning Elective (see below)
H&SS Elective**
H&SS 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-2400 Models of Computation
CSCI-4020 Computer Algorithms
CSCI-4290 Robot Motion Planning
CSCI-4380 Database Systems
CSCI-4390 Database Mining
CSCI-4600 The Human Computer Interface
CSCI-4999 Machine Learning in Bioinformatics
CSCI-4963 Data Mining
DSES-4810 Computational Intelligence
ECSE-4540 Introduction to Voice and Image Processing
PHIL-2140 Introduction to Logic
PHIL-4260 Philosophy of Artificial Intelligence
PHIL-4380 Philosophy of Mathematics
PHIL-4420 Computability and Logic
PHIL-4440 Knowledge, Belief and Cognition or Theory of Knowledge
PHIL-6240 Logic and Artificial 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
|
