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syllabus

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Overview

Description

The course objectives are to learn the fundamental theories, algorithms and representational structures underlying Artificial Intelligence. Class discussions will range from algorithm fundamentals to philosophical issues in Artificial Intelligence. Programs implementing problem-solving search, logical reasoning. and machine learning techniques will be studied and modified. Other topics will be covered as time permits. Students must complete a number of written and programming assignments and a semester project. During the last week of class, semester projects will be presented by students.

We will be using Python for assignment solutions. You may download and install Python on your computer, and work through the on-line tutorials to help prepare for this course. Experience with writing Python programs is not expected but helpful; an introduction to Python will be presented during the first few weeks of the semester.

Class meetings will be a combination of lectures by the instructor and discussions of your questions. You are expected to have read the assigned material before each class meeting. All questions are welcome, no matter how simple you think they are; it is always true that someone else has a similar question. Do not expect to be able to complete all assignments working on your own and not asking any questions. If you find yourself wondering what the next step is in finishing an assignment, visit or e-mail the instructor or the graduate teaching assistant. You may also discuss assignments with other students, but your code must be written by you.

You are expected to be familiar with the CS Department policy on cheating and with the CS Department Code of Ethics. This course will adhere to the CSU Academic Integrity Policy as found in the General Catalog and the Student Conduct Code. At a minimum, violations will result in a grading penalty in this course and a report to the Office of Conflict Resolution and Student Conduct Services.

A lot of material will be covered in this course. Students are expected to speak up in class with questions and observations they have about the material. Do not expect to be able to complete all assignments working on your own and without asking any questions. If you find yourself wondering what the next step is in finishing an assignment, please feel free to e-mail the instructor. You may also discuss assignments with other students, but your code and report must be written by you.

Time and Place

Class meets every Tuesday and Thursday, 11:00 am - 12:15 am, in Clark A 104. On-campus and distance-learning students will be able to watch video recordings of lectures.

Prerequisites

CS320 with a grade of C or better.

Textbook

Instructors

Office Hours Contact
Chuck Anderson Computer Science Building (CSB) Room 444 Tuesdays 1-2, Thursdays 2-3 chuck.anderson@colostate.edu
970-491-7491
GTA: Dejan Markovikj Room 235 491-2556
GTA: Kartikay Sharma Room 335 491-6275

Grading

Details of the course grading policy will be posted here.

syllabus.1502814945.txt.gz · Last modified: 2017/08/15 10:35 by anderson