COURSE UNIT TITLE

: ARTIFICIAL INTELLIGENCE WITH APPLICATIONS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
FSH 0057 ARTIFICIAL INTELLIGENCE WITH APPLICATIONS ELECTIVE 0 2 0 2

Offered By

Faculty Of Science

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR KADRIYE FILIZ BALBAL

Offered to

Biology
Chemistry
Computer Science
Statistics
Mathematics
Physics

Course Objective

The aim of this course is to have knowledge about the development and basic algorithms of Artificial Intelligence and to gain the ability to practice using artificial intelligence techniques.

Learning Outcomes of the Course Unit

1   To have knowledge about the definition of artificial intelligence
2   To be able to comprehend basic artificial intelligence algorithms
3   To be able to apply algorithmic solution methods
4   To be able to determine the appropriate artificial intelligence techniques for the problem
5   To be able to interpret by applying artificial intelligence methods

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 Programs Used in Artificial Intelligence Applications
3 Standardization Methods
4 Classification Algorithms-1
5 Classification Algorithms-2
6 Regression Algorithms
7 Support Vector Machines
8 Applications
9 Artificial Neural Networks-1
10 Artificial Neural Networks-2
11 Clustering Algorithms
12 Project Presentations
13 Project Presentations
14 Project Presentations

Recomended or Required Reading

Textbook(s):
Russell, S.J. And Norvig, P., Artificial Intelligence : A Modern Approach, Third Edition.

Supplementary Book(s):
Tom M. Mitchell, Machine Learning, McGraw Hill, 1997

Planned Learning Activities and Teaching Methods

The course will continue in the form of lectures, homework presentations and discussion by enriching the theoretical content with applications. In addition to the lesson taught, presentations will be prepared in groups and presented in the form of discussion sessions. In some weeks of the course, the results of the previous homework will be discussed and reinforced.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 FIN FINAL EXAM
3 FCGR FINAL COURSE GRADE (RESIT) ASG * 0.60 + FIN * 0.40
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) ASG * 0.60 + RST * 0.40


Further Notes About Assessment Methods

None

Assessment Criteria

Exams, assignments

Language of Instruction

Turkish

Course Policies and Rules

Homework submission must be done on time.

Contact Details for the Lecturer(s)

kadriyefiliz.balbal@deu.edu.tr

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 2 26
Preparations before/after weekly lectures 12 2 24
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 54

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13
LO.145543
LO.24445
LO.355555
LO.445554
LO.54455534

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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