IT Concentration: Machine and Computational Learning
(Science)
For those entering the program Fall 2007 semester & beyond
Contact Person: 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.
Required Courses:
| Semester I |
Semester II |
|
ITEC-1961 Introduction to Information Technology
ITEC-1220 Politics and Economics of IT
CSCI-1100 Computer Science I
MATH-1010 Calculus I
|
CSCI-1200 Computer Science II
MATH-2800 Intro to Discrete Structures
Life Science Elective (BIOL-XXXX)
Physical Science Elective (PHYS-XXXX)
|
| Semester III |
Semester IV |
|
ITEC-1150 Introduction to UML
ITEC-2961 Creativity and IT
CSCI-2300 Data Structures & Algorithms
Machine Learning Elective*
H&SS Elective**
|
ITEC-2110 Web Systems Development
ITEC-2210 Intro to Human Computer Interaction
CSCI-2500 Computer Organization
Free Elective
|
| Semester V |
Semester VI |
|
ITEC-4310 Managing IT Resources
DSES-4750 Probability Theory & Applications
Machine Learning Elective*
H&SS Elective**
|
IT Elective (one of):
- CSCI-4380 Database Systems
- MGMT-496X Data Resource Management
CSCI-4150 Intro to Artificial Intelligence
Machine Learning Elective*
H&SS Elective**
|
| Semester VII |
Semester VIII |
|
ITEC-4100 IT Capstone Experience
Machine Learning Elective*
Machine Learning Elective*
Free Elective
|
DSES-4810 Computational Intelligence
Machine Learning Elective*
H&SS Elective**
Free Elective
|
Students must satisfy an 8-credit communication requirement. See your advisor for details.
*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
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
|
