Nevşehir Hacı Bektaş Veli University Course Catalogue

Information Of Programmes

VOCATIONAL SCHOOL OF HACI BEKTAŞ VELİ / BİL220 - COMPUTER PROGRAMMING

Code: BİL220 Course Title: ARTIFICIAL_INTELLIGENCE Theoretical+Practice: 2+1 ECTS: 4
Year/Semester of Study 2 / Spring Semester
Level of Course Short Cycle Degree Programme
Type of Course Optional
Department COMPUTER PROGRAMMING
Pre-requisities and Co-requisites None
Mode of Delivery Face to Face
Teaching Period 14 Weeks
Name of Lecturer ORÇUN BAĞRA (orcunbagra@nevsehir.edu.tr)
Name of Lecturer(s)
Language of Instruction Turkish
Work Placement(s) None
Objectives of the Course
It is aimed to provide students to learn the basic concepts of artificial intelligence in search, play, logic, learning.

Learning Outcomes PO MME
The students who succeeded in this course:
LO-1 Learn the concepts of intelligence and artificial intelligence PO-51 Have knowledge about artificial intelligence.
Examination
Term Paper
LO-2 Students have knowledge about artificial intelligence applications PO-51 Have knowledge about artificial intelligence.
Examination
Term Paper
LO-3 Learning to search, play games, agents PO-51 Have knowledge about artificial intelligence.
Examination
Term Paper
LO-4 Learn about machine learning, classification and clustering PO-51 Have knowledge about artificial intelligence.
Examination
Term Paper
PO: Programme Outcomes
MME:Method of measurement & Evaluation

Course Contents
Concepts of intelligence and artificial intelligence, search algorithms, intelligent agents, machine learning, classification, clustering, artificial neural networks, genetic algorithms, fuzzy logic
Weekly Course Content
Week Subject Learning Activities and Teaching Methods
1 Introduction to artificial intelligence Narration, Question-Answer.
2 Intelligent agents Narration, Question-Answer.
3 Search algorithms Narration, Question-Answer.
4 Machine Learning – Normalization Narration, Question-Answer.
5 Classification, confusion matrix Narration, Question-Answer.
6 Clustering, contingency matrix Narration, Question-Answer.
7 Genetic Algorithms Narration, Question-Answer.
8 mid-term exam
9 Genetic Algorithms Narration, Question-Answer.
10 Artificial Neural Networks Narration, Question-Answer.
11 Artificial Neural Networks Narration, Question-Answer.
12 Fuzzy Logic Narration, Question-Answer.
13 Students Presentations Narration, Question-Answer.
14 Students Presentations Narration, Question-Answer.
15 Students Presentations Narration, Question-Answer.
16 final exam
Recommend Course Book / Supplementary Book/Reading
1 Russell, S.J. And Norvig, P., “Artificial Intelligence : A Modern Approach”, Third Edition, Prentice-Hall, 2009. (AIMA)
2 Sunumlar
3 Yapay Zeka Uygulamaları, Seçkin Yayıncılık, 2016
Required Course instruments and materials
Course book, laptop computer, projector

Assessment Methods
Type of Assessment Week Hours Weight(%)
mid-term exam 8 1 20
Other assessment methods
1.Oral Examination
2.Quiz
3.Laboratory exam
4.Presentation
5.Report
6.Workshop
7.Performance Project
8.Term Paper 15 1 20
9.Project
final exam 16 1 60

Student Work Load
Type of Work Weekly Hours Number of Weeks Work Load
Weekly Course Hours (Theoretical+Practice) 4 14 56
Outside Class
       a) Reading 3 8 24
       b) Search in internet/Library 3 7 21
       c) Performance Project 0
       d) Prepare a workshop/Presentation/Report 0
       e) Term paper/Project 2 4 8
Oral Examination 0
Quiz 0
Laboratory exam 0
Own study for mid-term exam 2 2 4
mid-term exam 1 1 1
Own study for final exam 2 2 4
final exam 2 1 2
0
0
Total work load; 120