Computer Programming (Evening Education) Preview
Associate	TR-NQF-HE: Level 5	QF-EHEA: Short Cycle	EQF-LLL: Level 5

Course Introduction and Application Information

Course Code:

UNI253

Course Name:

Decision Making and Problem Solving Techniques

Semester:

Fall

Course Credits:

ECTS

Language of instruction:

Turkish

Course Condition:

Does the Course Require Work Experience?:

Type of course:

University Elective

Course Level:

Associate

TR-NQF-HE:5. Master`s Degree

QF-EHEA:Short Cycle

EQF-LLL:5. Master`s Degree

Mode of Delivery:

E-Learning

Course Coordinator:

Dr. Öğr. Üy. TAYFUN UTAŞ

Course Lecturer(s):

Tayfun Utaş

Course Assistants:

Course Objective and Content

Course Objectives:	The aim of this course is to provide students with the ability to analyze complex decision-making processes and produce solutions. Throughout the course, students will understand decision-making processes through statistical and optimization models, develop their analytical thinking skills and have the opportunity to apply problem-solving techniques.
Course Content:	1. Decision Making Process and Models 2. Statistical Decision Making Techniques 3. Optimization Models and Solution Techniques 4. Problem Solving Approaches and Techniques 5. Real Life Applications of Decision Making and Problem Solving Techniques

Learning Outcomes

The students who have succeeded in this course;
1) Ability to understand and analyze decision-making processes and models.
2) Ability to analyze data through statistical and optimization models.
3) Developing analytical thinking abilities.
4) Ability to apply effective problem solving techniques.
5) Ability to apply decision-making and problem-solving techniques to real-life situations.

Course Flow Plan

Week	Subject	Related Preparation
1)	Introduction to Decision Making Process and Models
2)	Statistical Decision Making Techniques - I
3)	Statistical Decision Making Techniques - II
4)	Introduction to Optimization Models
5)	Optimization Solution Techniques - I
6)	Optimization Solution Techniques - II
7)	Introduction to Problem Solving Approaches
8)	Midterm exam
9)	Problem Solving Techniques - I
10)	Problem Solving Techniques - II

Sources

Course Notes / Textbooks:	1. Bazerman, M.H. & Moore, D.A. (2012). Judgment in Managerial Decision Making. Wiley. 2. Dyer, J.S. & Watson, G. (2013). Analytic Decision Making. Springer.
References:	1. Hammond, J.S., Keeney, R.L., & Raiffa, H. (2006). Smart Choices: A Practical Guide to Making Better Decisions. Broadway Business. 2. Ullman, D.G. (2010). The Mechanical Design Process. McGraw-Hill.

Course - Program Learning Outcome Relationship

Course Learning Outcomes	1	2	3	4	5
Program Outcomes
1) He gains the ability of problem solving and analytical thinking skills.
2) He learns the fundamentals of computer programming, hardware and software and the basic computer concepts.
3) He develops algorithms according to the problems, gains the ability to distinguish the appropriate ones from the fundamental algorithms for the problem.
4) He understands object-oriented programming concept and web programming.
5) He learns radix systems, fundamental electronics and computer hardware knowledge.
6) He gains mobile programming skills and develops applications for mobile platforms.
7) He designs and codes databases.
8) He learns to program and use computer networks, open source operating systems.
9) He uses the English language effectively.
10) He learns to use appropriate data structures according to programming requirements.
11) He develops software individually or as a team.
12) He follows developments in the field, high technology tools / applications.
13) He gains awareness of professional and ethical responsibility and has an awareness of professional ethics.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Average	3 Highest

	Program Outcomes	Level of Contribution
1)	He gains the ability of problem solving and analytical thinking skills.	1
2)	He learns the fundamentals of computer programming, hardware and software and the basic computer concepts.	1
3)	He develops algorithms according to the problems, gains the ability to distinguish the appropriate ones from the fundamental algorithms for the problem.	1
4)	He understands object-oriented programming concept and web programming.	2
5)	He learns radix systems, fundamental electronics and computer hardware knowledge.	2
6)	He gains mobile programming skills and develops applications for mobile platforms.	2
7)	He designs and codes databases.	2
8)	He learns to program and use computer networks, open source operating systems.	2
9)	He uses the English language effectively.	1
10)	He learns to use appropriate data structures according to programming requirements.	1
11)	He develops software individually or as a team.	2
12)	He follows developments in the field, high technology tools / applications.	2
13)	He gains awareness of professional and ethical responsibility and has an awareness of professional ethics.	2

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Midterms	1	% 40
Final	1	% 60
total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
total		% 100

Workload and ECTS Credit Calculation

Activities	Number of Activities	Preparation for the Activity	Spent for the Activity Itself	Completing the Activity Requirements	Workload
Course Hours	14	3	2		70
Midterms	1	20	2		22
Final	1	30	3		33
Total Workload					125