Visual Communication Design Preview
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code:

UNI220

Course Name:

Machine Learning and Data Science

Semester:

Spring

Course Credits:

ECTS

Language of instruction:

Turkish

Course Condition:

Does the Course Require Work Experience?:

Type of course:

University Elective

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

E-Learning

Course Coordinator:

Dr. Öğr. Üy. ALPER ÖNER

Course Lecturer(s):

Ferzat Anka

Course Assistants:

Course Objective and Content

Course Objectives:	The aim of the course is to provide students with information on basic techniques and methods in artificial learning and to enable students to have the ability to use artificial learning methods in solving practical problems. At the same time, it is to understand the importance of machine learning in today's application areas.
Course Content:	Machine learning basic concepts and methods. Problem solving using machine learning; methods using and not using problem information. Data analysis, To examine various algorithms. To explain the importance of artificial intelligence methods in different fields with examples

Learning Outcomes

The students who have succeeded in this course;
1) • Recognize the problems that can be solved by machine learning methods.
2) • Understanding the importance of artificial intelligence in solving various problems
3) • Can choose the appropriate machine learning method for the given problem.
4) • Can solve the given problem with the appropriate machine learning method.
5) • Knows the ways of representing information, its advantages and disadvantages.

Course Flow Plan

Week	Subject	Related Preparation
1)	Machine learning history and philosophy
2)	Basic concepts
3)	Basic concepts-Intelligent Agents
4)	Introduction to machine learning and problem solving and search algorithms
5)	Expert systems and machine learning
6)	Optimization methods in machine learning
7)	Homework-Presentation
8)	Homework-Presentation
9)	Homework-Presentation
10)	Data science and analysis
11)	Machine learning
12)	Data science and methods
13)	Machine learning
14)	Search algorithms and their importance (Definite, greedy, heuristic, meta-heuristic)

Sources

Course Notes / Textbooks:

• Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Ed., Prentice Hall, 2010,
• Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition) 3rd Edition
• Vasif Nabiyev, Yapay Zeka: İnsan ve Bilgisayar Etkileşimi 4. Baskı
• Yalçin Özkan, Veri Madenciliği Yöntemleri, Papatya, 2008
• Cemalettin Kubat, Matlab Yapay Zeka ve Mühendislik uygulamaları, Pusula, 2009
• İlker Arslan, R ile İstatistiksel Programlama, Pusula, 2020
• Zafer Demirkol, Herkes İçin Yapay Zeka, Genç Destek, 2021
• S.Nematzadeh et al. Rationalized Statistics for Biosciences Analysing bioinformatics data using the R, LAP Publishing, 2021

References:

Course - Program Learning Outcome Relationship

Course Learning Outcomes	1	2	3	4	5
Program Outcomes
1) To understand the structure and dynamics of a design team and to continue the production processes in a flow with team members from different disciplines.
1) To have the necessary knowledge and skills about computer technologies required to produce designs.
1) To be able to manage the design, development and presentation processes by applying the right theoretical steps and to be involved in the production process from start to finish.
1) To be able to criticize and evaluate different problems through these concepts by mastering the design processes.
1) To understand the conceptual importance of Visual Communication Design and to gain the ability to develop user-centered experience-oriented designs.
2) To be able to create balanced interactive narratives with communication and design processes by understanding the ways in which visual designs convey ideas, messages and emotions in experience.
2) To be able to analyze, evaluate and interpret the situations and facts about design issues by using different disciplines.
3) To be able to develop professional projects by producing components for different media, to evaluate these components consistently in the context of the designs developed.
3) To be able to analyze and use design-oriented thinking processes for visual communication products.
4) To have the necessary computer technologies and software knowledge to develop design in line with the needs of the sector, to be able to use computer-aided design applications to reflect their creative ideas.
4) To be able to use these designs effectively in the context of theme, subject and target audience by applying effective visual and audio solutions for communication design products.
5) Mastering contemporary design methodology; To produce designs that appeal to the audience by prioritizing the target audience of the designs.
6) To understand the experience of the users and the target audience, to understand the measurement methods and to benefit from these concepts in the design process.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Average	3 Highest

	Program Outcomes	Level of Contribution
1)	To understand the structure and dynamics of a design team and to continue the production processes in a flow with team members from different disciplines.
1)	To have the necessary knowledge and skills about computer technologies required to produce designs.
1)	To be able to manage the design, development and presentation processes by applying the right theoretical steps and to be involved in the production process from start to finish.
1)	To be able to criticize and evaluate different problems through these concepts by mastering the design processes.
1)	To understand the conceptual importance of Visual Communication Design and to gain the ability to develop user-centered experience-oriented designs.
2)	To be able to create balanced interactive narratives with communication and design processes by understanding the ways in which visual designs convey ideas, messages and emotions in experience.
2)	To be able to analyze, evaluate and interpret the situations and facts about design issues by using different disciplines.
3)	To be able to develop professional projects by producing components for different media, to evaluate these components consistently in the context of the designs developed.
3)	To be able to analyze and use design-oriented thinking processes for visual communication products.
4)	To have the necessary computer technologies and software knowledge to develop design in line with the needs of the sector, to be able to use computer-aided design applications to reflect their creative ideas.
4)	To be able to use these designs effectively in the context of theme, subject and target audience by applying effective visual and audio solutions for communication design products.
5)	Mastering contemporary design methodology; To produce designs that appeal to the audience by prioritizing the target audience of the designs.
6)	To understand the experience of the users and the target audience, to understand the measurement methods and to benefit from these concepts in the design process.

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Presentation	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	Workload
Course Hours	16	48
Study Hours Out of Class	16	53
Presentations / Seminar	5	10
Final	1	2
Total Workload		113