Time/Place: MWF 12:30am - 12:18pm, BE 0184
Instructor: Venu Satuluri
Office: DL686 (Data Mining Research Lab)
Email: lastname at cse.ohio-state.edu (lastname==satuluri)
Office Hours: Tuesday, Thursday 11:30am - 12:30pm
Grader: Joel McCance
Grader Email: lastname.10@osu.edu (lastname=mccance)
Grader Office hours: (Office: CL 420), 1:30pm - 2:20pm Wednesdays

Course Description:
A survey of the basic concepts and techniques of problem solving paradigms and knowledge representation schemes in Artificial Intelligence (AI).

Course Objectives:
Upon satisfactory completion of the course, the student will have learned:

• AI terminology
• Fundamentals of AI problem solving
• Fundamentals of Knowledge Representation
• Fundamentals of Machine Learning

Prerequisites: CSE 222 and Math 366

Text book: Russell and Norvig, Artificial Intelligence: A Modern Approach, Second Edtition, Prentice Hall

Grading Plan:
Midterm - 30%
Final - 40%
Homeworks - 30%

Homeworks:
There will be 6 homeworks in the course, out of which the homework with the lowest course will be dropped i.e. only the best 5 homeworks will be used for calculating your grade. For programming assignments, your programs will have to work on the CSE unix machines stdsun or stdlogin - this is a must. If you are unaware of how to compile your programs on unix/linux environments, or how to use a unix/linux environments in general, this is a good opportunity for you to learn how to do so.

Policy:
No late homework or lab is accepted without substantial documentation of the reason. Excuse from scheduled exams can be accepted only in case of personal sickness requiring medical care or severe accidents in the immediate family.

Course Material:
The course material - slides, homeworks etc. - will be posted on Carmen.

630 Tentative Schedule: