COURSE UNIT TITLE

: INTELLIGENT SYSTEMS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
BIS 5008 INTELLIGENT SYSTEMS ELECTIVE 3 0 0 5

Offered By

Business Information Systems (English)

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR SABRI ERDEM

Offered to

Business Information Systems (English)

Course Objective

It is aimed to provide students with an understanding of intelligent systems in business information systems.

Learning Outcomes of the Course Unit

1   Demonstrate an understanding the theories and concepts of intelligent systems
2   Build data mining and business intelligence models.
3   Design an intelligent system model for an enterprise.
4   Apply techniques to real world cases.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction
2 Expert Systems
3 Neural Networks
4 Genetic Algorithms
5 Artificial Intelligence and Machine Learning
6 Data Mining: Understanding and Exploring Data
7 Data Mining: Modeling, Validation and Reporting
8 Midterm Exam
9 Business Intelligence: OLAP Cubes
10 Business Intelligence: Model Building
11 Business Intelligence: Real World Applications
12 Business Intelligence: Real World Applications
13 Term Project Presentations
14 Term Project Presentations

Recomended or Required Reading

Any material (books, articles) on intelligent systems.

Planned Learning Activities and Teaching Methods

Lecture, group work, presentations, class discussions, field study

Assessment Methods

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


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

1. Midterm and Final Exam: Students will be assessed on their knowledge of concepts and theories through an essay-type written exam semester
2. Term Project: Groups will do an observation in a real business environment about intelligent systems and prepare a written report based on the format given by the instructor. They are expected to share their observation with their class-mates through oral presentations.
3. Class Discussions and Presentation: Students will be given certain cases or questions related to the concepts covered in the class. Groups will debate on the topics and present their opinions. Students are expected to contribute to class discussions.

Language of Instruction

English

Course Policies and Rules

1. Attending at least 70 percent of lectures is mandatory.
2. Plagiarism of any type will result in disciplinary action.
3. Students are expected to participate actively in class discussions.
4. Students are expected to attend to classes on time.
5. Students are expected to prepare ahead of time for class.

Contact Details for the Lecturer(s)

sabri.erdem@deu.edu.tr

Office Hours

To be announced at the first lecture.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 11 1 11
Preparation for midterm exam 1 20 20
Preparation for final exam 1 20 20
Preparing assignments 1 30 30
Preparing presentations 5 2 10
Final 1 3 3
Midterm 1 3 3
TOTAL WORKLOAD (hours) 136

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7
LO.155
LO.255555
LO.355555
LO.455555