CSCI-736: NEURAL NETWORKS AND MACHINE LEARNING

RIT Department of Computer Science

Catalogue Description

The course will introduce students into the current state of artificial neural networks. It will review different application areas such as intrusion detection and monitoring systems, pattern recognition, access control and biological authentication, and their design. The students will be required to conduct research and analysis of existing applications and tools as well as to implement a course programming project on design of a specified application based on neural networks and/or fuzzy rules systems. (CSCI-630 or CSCI-331 or permission of  instructor)

Class 2.5, Lab 0.5, Credit 3 (Spring)

Course Outcomes

• Students will be able to advance their theoretical knowledge of artificial intelligence methodologies in different applications. (supports program outcome 2) Evaluation: Assessed by project report and tests
• Students will be able to learn the structure and design concepts of neural networks applications. (supports program outcome 2) Evaluation: Assessed by project report and tests
• Students will be able to advance their communication and presentation skills. (supports program outcomes 3 and 4) Evaluation: Assessed by  a presentation on the topic assigned
• Students will be able to advance their research and analytical skills. (supports program outcome 4) Evaluation: Assessed by a project report and a presentation

Instructor Contact

Course Policies

This class will be taught in a blended mode; the class meeting time will be reduced but the students shall do more work independently and online

Required Materials

Lecture notes and other materials on myCourses

Additional Resources

Textbook: J.C.Principe, N.R.Euliaon, W. Curf Lefebvre “Neural and Adaptive systems” John Wiley and Sons

Grading

• Rescheduling an Exam

• Course Withdrawal

• Disability Services

• Academic Integrity

updated: Monday April 16 12:08:00 EDT 2012