Political Science and Public Administration 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 have knowledge about the basic theoretical debates in Political Science and Public Administration.
2) To define contemporary developments, approaches and basic concepts in Political Science and Public Administration at national and international level.
3) Relate the interaction of the Department of Political Science and Public Administration with other social sciences (philosophy, history, sociology, law, economy, business).
4) Evaluate and discuss the events in interdisciplinary dimension, acquire knowledge and skills, conduct research using social sciences methods and follow the field.
5) Political and social processes that take place in Turkey and in the world, able to solve problems and the causes of these problems, on the relationship of citizens with political structures reveals scientifically.
6) To design and to prepare scientific studies such as theoretical or experimental projects, reports, articles and theses, either on their own or with others, and uses qualitative and quantitative research techniques related to their field.
7) To use leadership characteristics in Political Science and Public Administration with the awareness of compliance with team work.
8) Develops behavior according to ethics and social values and evaluates what they have learned by deciding what they need and critically question the information they have acquired.
9) Transmits the opinions, thoughts and solutions in Political Science and Public Administration to the related persons and institutions in written and oral form.
10) According to the level of European Language Portfolio, a foreign language is at least A2 for Pre-Bachelor's degree according to the level of education; At least B1 for the License; To be able to use at least C1 and at least C1 General Level for PhD.
11) To be able to use information and communication technologies together with computer software in at least the European Computer Driving License Basic Level (Associate) or Advanced Level (Associate and Associate) required by the department.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Average	3 Highest

	Program Outcomes	Level of Contribution
1)	To have knowledge about the basic theoretical debates in Political Science and Public Administration.	1
2)	To define contemporary developments, approaches and basic concepts in Political Science and Public Administration at national and international level.	1
3)	Relate the interaction of the Department of Political Science and Public Administration with other social sciences (philosophy, history, sociology, law, economy, business).	3
4)	Evaluate and discuss the events in interdisciplinary dimension, acquire knowledge and skills, conduct research using social sciences methods and follow the field.	3
5)	Political and social processes that take place in Turkey and in the world, able to solve problems and the causes of these problems, on the relationship of citizens with political structures reveals scientifically.	3
6)	To design and to prepare scientific studies such as theoretical or experimental projects, reports, articles and theses, either on their own or with others, and uses qualitative and quantitative research techniques related to their field.	2
7)	To use leadership characteristics in Political Science and Public Administration with the awareness of compliance with team work.	2
8)	Develops behavior according to ethics and social values and evaluates what they have learned by deciding what they need and critically question the information they have acquired.	2
9)	Transmits the opinions, thoughts and solutions in Political Science and Public Administration to the related persons and institutions in written and oral form.	1
10)	According to the level of European Language Portfolio, a foreign language is at least A2 for Pre-Bachelor's degree according to the level of education; At least B1 for the License; To be able to use at least C1 and at least C1 General Level for PhD.	2
11)	To be able to use information and communication technologies together with computer software in at least the European Computer Driving License Basic Level (Associate) or Advanced Level (Associate and Associate) required by the department.	2

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