Course Code	Semester	Course Name	LE/RC/LA	Course Type	Language of Instruction	ECTS
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Course Goals	To teach fundamentals of machine learning and artificial intelligence and provide students with capability of using this knowledge for pattern recognition.
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Teaching Methods and Techniques
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Course Schedules
Week	Contents	Learning Methods
1. Week	Fundementals of machine learining, working with data and pre-processing	disclosure
2. Week	Python Anaconda distribution, Jupyter usage and introduction to required libraries	disclosure
3. Week	Linear regression and multiple regression	computer aided application
4. Week	kNN, feature selection and classification performance	computer aided application
5. Week	Navie Bayes classification	computer aided application
6. Week	Logistic Regression	computer aided application
7. Week	Support Vector Machines	computer aided application
8. Week	Midterm Exam
9. Week	Midterm Exam
10. Week	Decision Trees and Ensembling Methods (CART, RF and GBC)	Student presentations
11. Week	Unsupervised Learning and Clustering	computer aided application
12. Week	Deep learning and Artificial Neural Networks-1	computer aided application
13. Week	Deep learning and Artificial Neural Networks-2	computer aided application
14. Week	Deep learning and Artificial Neural Networks-3	computer aided application
15. Week	Final Exam
16. Week	Final Exam
17. Week

Assessments
Evaluation tools	Quantity	Weight(%)
Homework / Term Projects / Presentations	1	50
Final Exam	1	50

Program Outcomes PO-1 To identify and use theoretical and practical knowledge in International Relations. PO-2 To express ideas and assessments about contemporary debates in International Relations. PO-3 To acknowledge ethical and scientific responsibilities of data collection, evaluation and publication. PO-4 To monitor and interpret published studies in International Relations. PO-5 To use a second language at an intermediate level. PO-6 To analyze, compare and relate different local, regional and global developments in International Relations. PO-7 To analyze, compare and relate International Relations with theories and practices of different associate departments and their sub-fields and to offer suggestions by combining these fields. PO-8 To present substantial knowledge for various public, private and academic career positions. PO-9 To analyze the emergence and functions of prominent regional and local actors and to make future projections about their actions. PO-10 To theoretically and practically examine different events and facts in International Relations and Foreign Policy and to interpret their past, present, and future through a scientific perspective.

Learning Outcomes LO-1 Solve complex problems with aid of computer LO-2 To process data LO-3 To infer results from data LO-4 To be able to use data to foresight and prediction LO-5 To develop artificial intelligence applications

Course Assessment Matrix:

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