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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS YBS 4015 ARTIFICIAL INTELLIGENCE ELECTIVE 3 0 0 4

Offered By

Management Information Systems

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR KUTAN KORUYAN

Offered to

Management Information Systems

Course Objective

The purpose of this course is to provide students systems through which students can control and track administrative activities automatically using information systems.

Learning Outcomes of the Course Unit

1   will manage decision-making processes effectively 2   will introduce computers experiences previosly obtained from complex and independent of each other problems and use it for solution of other problems. 3   Will provide implementation by computer automatizing many administrative processes.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to Artificial Intelligence 2 Artificial Intelligence History and Definitions 3 Expert Systems 4 Robotics 5 Fuzzy Logic 6 Machine Learning 7 Machine Learning II 8 Artificial Neural Networks 9 Genetic Algorithms 10 Pattern Recognition 11 Natural Language Processing 12 Student Presentations 13 Student Presentations 14 Student Presentations

Recomended or Required Reading

Main Reference: Lucci S. (2012). Artificial Intelligence in the 21st Century.Mercury Learning & Information. Luger G. F.(2008). Artificial Intelligence: Structures and Strategies for Complex Problem Solving. Addison-Wesley. Subsidiary References: Russell S. & Norvig P.(2009).Artificial Intelligence: A Modern.

Planned Learning Activities and Teaching Methods

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 STT TERM WORK (SEMESTER) 2 MTE MIDTERM EXAM 3 MTEG MIDTERM GRADE STT * 0.50 +MTE * 0.50 4 FIN FINAL EXAM 5 FCG FINAL COURSE GRADE MTEG * 0.40 + FIN * 0.60 6 RST RESIT 7 FCGR FINAL COURSE GRADE (RESIT) MTEG * 0.40 + RST * 0.60 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

Success of students will be evaluated according to mid-term and final exam.

Assessment Criteria

Students will undergo two exams, one mid-term and one final.

Language of Instruction

Turkish

Course Policies and Rules

The rules applied by the department is valid.

Contact Details for the Lecturer(s)

will be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 12 3 36 Preparation for midterm exam 1 10 10 Preparations before/after weekly lectures 12 3 36 Preparation for final exam 1 15 15 Final 1 1 1 Midterm 1 1 1 TOTAL WORKLOAD (hours) 99

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 LO.1 5 5 5 5 5 5 5 LO.2 5 5 5 5 5 5 5 LO.3 5 5 5 5 5 5 5