UNI220 Machine Learning and Data ScienceIstinye UniversityDegree Programs Public Relations and AdvertisingGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
Public Relations and Advertising

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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: Fall
Course Credits:
ECTS
5
Language of instruction: Turkish
Course Condition:
Does the Course Require Work Experience?: No
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: • 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

Course - Program Learning Outcome Relationship

Course Learning Outcomes

1

2

3

4

5

Program Outcomes
1) They have all the knowledge, skills and competencies required by the profession, with relation to the fields of Public Relations and Advertising and they have the structural features required by the profession.
2) They have knowledge about fields of brand management, marketing communication, corporate communication and advertising strategy development. They have the ability to create, plan and manage a public relations campaign.
3) They have knowledge and skills about changing and evolving communication methods and technologies.
4) Thay have the ability to manage communication between relevant stakeholders and the target group. They develop and implement proper communication strategies and methods according to the communication characteristics of different stakeholders.
5) By acting on the principle of lifelong learning, they constantly develop themselves not only from in terms of professional knowledge, but also from a culturally and follow the national and international agenda.
6) They combine different communication areas in a holistic and strategic way.
7) They use written and verbal communication skills effectively.
8) They develop and implement strategies by thinking creatively and critically.
9) They have management skills.
10) They use research capability effectively.
11) They have an ethical business understanding and social responsibility.
12) They have capable of analytical thinking and problem solving.
13) They have teamwork skills.
14) They follow developments in their field by using a foreign language at a general level of European Language Portfolio B1 and and communicate with their colleagues.
15) They use information and communication technologies together with computer software at the advanced level of European Computer Driving License required by the field.

Course - Learning Outcome Relationship

No Effect 1 Lowest 2 Average 3 Highest
       
Program Outcomes Level of Contribution
1) They have all the knowledge, skills and competencies required by the profession, with relation to the fields of Public Relations and Advertising and they have the structural features required by the profession.
2) They have knowledge about fields of brand management, marketing communication, corporate communication and advertising strategy development. They have the ability to create, plan and manage a public relations campaign.
3) They have knowledge and skills about changing and evolving communication methods and technologies.
4) Thay have the ability to manage communication between relevant stakeholders and the target group. They develop and implement proper communication strategies and methods according to the communication characteristics of different stakeholders.
5) By acting on the principle of lifelong learning, they constantly develop themselves not only from in terms of professional knowledge, but also from a culturally and follow the national and international agenda.
6) They combine different communication areas in a holistic and strategic way.
7) They use written and verbal communication skills effectively.
8) They develop and implement strategies by thinking creatively and critically.
9) They have management skills.
10) They use research capability effectively.
11) They have an ethical business understanding and social responsibility.
12) They have capable of analytical thinking and problem solving.
13) They have teamwork skills.
14) They follow developments in their field by using a foreign language at a general level of European Language Portfolio B1 and and communicate with their colleagues.
15) They use information and communication technologies together with computer software at the advanced level of European Computer Driving License required by the field.

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