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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS YBS 4024 BUSINESS INTELLIGENCE ELECTIVE 3 0 0 4

Offered By

Management Information Systems

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR CAN AYDIN

Offered to

Management Information Systems

Course Objective

The aim of the course is to inform the students about current information about Artificial Neural Networks and Genetic Algorithms, to follow the new developments in this area and to improve their ability to use them in the solution of their problems

Learning Outcomes of the Course Unit

1   Comprehension of basic principles of artificial neural networks techniques 2   Comprehension of basic principles of genetic algorithm techniques 3   To be able to use the learned techniques as a tool in operations research problems 4   Understanding the difference between artificial neural networks and genetic algorithm techniques from classical methods to understand when and how they can work 5   To be able to produce effective solutions for some specific work life problems

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to Business Intelligence 2 Revision of database concepts on business intelligence. 3 Decision Support Systems and online analytical processing. 4 Multidimensional modeling and relational model.MySQL Trigger) 5 The use of multidimensional modeling in online analytical processing. 6 Introduction to information storage 7 Information storage design 8 Implementation of information storage 9 The use of SQL language on information storage 10 Introduction to data cubes 11 Reporting with data cubes 12 Reporting systems 13 Reporting systems 14 Ethical and legal aspects of business intelligence.

Recomended or Required Reading

To be announced.

Planned Learning Activities and Teaching Methods

Events are in "Assessment Methods" and "Workload Calculation" section detaily.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 MTEG MIDTERM GRADE MTEG * 1 3 FIN FINAL EXAM 4 FCGR FINAL COURSE GRADE MTEG * 0.40 + FIN * 0.60 5 RST RESIT 6 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

None

Assessment Criteria

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

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 12 4 48 Preparations before/after weekly lectures 12 4 48 Final 1 1 1 Midterm 1 1 1 TOTAL WORKLOAD (hours) 98

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 LO.2 5 5 5 LO.3 5 5 LO.4 5 5 5 LO.5 5 5 5