Course Learning Outcomes (CLOs) are those describing the knowledge, skills and competencies that students are expected to achieve upon successful completion of the course. In this context, Course Learning Outcomes defined for this course unit are as follows:
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| Knowledge
(Described as Theoritical and/or Factual Knowledge.)
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1) Explain the basic terminology in the fields related to data.
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| Skills
(Describe as Cognitive and/or Practical Skills.)
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1) Applies artificial intelligence concepts and techniques in different projects in the game.
2.1) Adapts the appropriate algorithm to the relevant game project in artificial intelligence problems and interprets different model success percentages.
2.2) Originally, synthesizes innovative game approaches in the field of artificial intelligence.
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| Competences
(Described as "Ability of the learner to apply knowledge and skills autonomously with responsibility", "Learning to learn"," Communication and social" and "Field specific" competences.)
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1) Takes responsibility in artificial intelligence projects in accordance with the target.
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2) Manages his time effectively in individual and team projects.
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| Week |
Subject |
Materials Sharing * |
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Related Preparation |
Further Study |
| 1) |
Introduction to Artificial Intelligence and History |
PPT
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| 2) |
Artificial Intelligence Fundamentals and Data Structures |
PPT
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| 3) |
CRISP-DM and Data Processing |
PPT
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| 4) |
Introduction to Machine Learning: Supervised and Unsupervised Learning |
PPT
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| 5) |
Linear / Logistic Regression |
PPT
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| 6) |
Naive Bayes and KNN Algorithms |
PPT
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| 7) |
SVM and Decision Tree Algorithms |
PPT
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| 8) |
Introduction to artificial neural networks: Structure and basic elements of artificial neural networks |
PPT
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| 9) |
Deep Learning Algorithms |
PPT
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| 10) |
Deep Q - learning |
PPT
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| 11) |
Analysis of Usage Examples of Artificial Intelligence in Games |
PPT
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| 12) |
Unity and Machine Learning Kit Introduction |
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| 13) |
Game Applications with Unity |
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| 14) |
Game Applications with Unity II |
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| Course Notes / Textbooks: |
-Ethem Alpaydin. 2004. Introduction to Machine Learning (Adaptive Computation and Machine Learning). The MIT Press.
- Balaban M.E., Kartal, E., “Veri Madenciliği ve Makine Öğrenmesi Temel Kavramlar,
Algoritmalar, Uygulamalar”, Kitap Editörlüğü , Çağlayan Kitabevi, İSTANBUL,
2019.
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| References: |
-Yannakakis, G. N. and Togelius, J. (2018). Artificial Intelligence and Games. Springer.
-Han, J., & Kamber, M. (2012). Data mining: Concepts and techniques (3rd ed). Elsevier.
-Safadi, F., Fonteneau, R., & Ernst, D. (2015). Artificial Intelligence in Video Games: Towards a Unified Framework. International Journal of Computer Games Technology, 2015, 271296.
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(KPLOs and SPLOs are the abbreviations for Key & Sub- Programme Learning Outcomes, respectively. )
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Programme Learning Outcomes |
Contribution Level (from 1 to 5) |
1) |
Defines the concepts of computer science and design techniques required in Digital Game Design. |
2 |
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1.1 Defines game design principles, game mechanics, dynamics and episode design concepts. |
2 |
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1.2 Lists drawing and animation techniques in the context of discipline. |
1 |
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1.3 Interprets the historical and theoretical information about analog and digital games. |
2 |
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2) |
Creates digital games supported with current technology and designs in line with the determined goals. |
2 |
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2.1 Organizes the digital game design process by planning and analyzing the situation. |
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2.2 Manages the digital game design process using interdisciplinary components. |
2 |
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2.3 Compiles and dramatizes written and visual stories using various tools. |
2 |
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2.4 Adapts the aesthetic and algorithmic components of digital games. |
5 |
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2.5 Uses the knowledge of writing code and animation for digital games designed to be offered on different platforms. |
2 |
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2.6 Uses artificial intelligence techniques in the game development process and calculates probabilities based on mathematics and physics rules. |
5 |
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2.7 Constructs the game design and game elements by using them in non-game areas. |
1 |
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3) |
Designs artistic structure to support digital game design. |
1 |
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3.1 Analyzes the design elements in the game using the theoretical knowledge. |
1 |
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3.2 Uses freehand drawing and digital drawing techniques. |
1 |
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3.3 lans the game design with visual and audio dimensions. |
1 |
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4) |
Analyzes the structures, logical framework and mechanisms of analog and digital games. |
1 |
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4.1 Identifies the problems encountered in the game design process. |
1 |
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4.2 Synthesizes the references to civilization history and mythology taken as reference in the game discipline according to the current game theory. |
1 |
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4.3 Plans the delivery of the product to the target audience in the right way. |
4 |
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5) |
S/he acquires the competencies that develop by the expectations of business world and the society defined as the institutional outcomes of our university on the advanced level in relation with his/her field. |
4 |
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5.1 Acquires the analyzing solving the problems and managing the conflicts. |
4 |
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5.2 Participates as a team member and takes responsibility in the environments that require the solving of the conflicts and acts as a leader when necessary. |
4 |
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5.3 Has awareness for ethical and social responsivity. |
4 |
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5.4 By supporting the learnt courses with quantitative and qualitative data; and by using verbal and visual communication means, s/he transfers them to the groups within and outside his/her group in a systematical and effective way. |
4 |
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5.5 Evaluates the norms and standards present in the works in which s/he takes responsibility in a critical point of view. |
4 |
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5.6 Develops strategical, innovative and entrepreneurial ideas. |
4 |
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5.7 Acquires competence of managing the change. |
2 |
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5.8 Shows development personally and socially with and awareness for lifelong learning. |
2 |
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5.9 Follows advanced technologies and developments about digital transformation. |
4 |
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5.10 Has cultural awareness and s/he transfers this to the groups within and outside his/her field. |
1 |
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5.11 Has awareness about citizenship competency. |
1 |
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5.12 Acquires communication in a Foreign Language (English) competence defined on the level of at least B1 in European Language Portfolio. (In programs whose medium of instruction is English, on the level of B2/B2+). |
4 |
| WORKLOAD OF TEACHING & LEARNING ACTIVITIES |
| Teaching & Learning Activities |
# of Activities per semester |
Duration (hour) |
Total Workload |
| Course |
14 |
4 |
56 |
| Laboratory |
0 |
0 |
0 |
| Application |
5 |
6 |
30 |
| Special Course Internship (Work Placement) |
0 |
0 |
0 |
| Field Work |
0 |
0 |
0 |
| Study Hours Out of Class |
0 |
0 |
0 |
| Presentations / Seminar |
0 |
0 |
0 |
| Project |
2 |
12 |
24 |
| Homework Assignments |
1 |
12 |
12 |
| Total Workload of Teaching & Learning Activities |
- |
- |
122 |
| WORKLOAD OF ASSESMENT & EVALUATION ACTIVITIES |
| Assesment & Evaluation Activities |
# of Activities per semester |
Duration (hour) |
Total Workload |
| Quizzes |
2 |
6 |
12 |
| Midterms |
1 |
5 |
5 |
| Semester Final Exam |
1 |
5 |
5 |
| Total Workload of Assesment & Evaluation Activities |
- |
- |
22 |
| TOTAL WORKLOAD (Teaching & Learning + Assesment & Evaluation Activities) |
144 |
| ECTS CREDITS OF THE COURSE (Total Workload/25.5 h) |
6 |
ECTS Information Package / Course Catalogue