Course Details

CORPORATE FINANCE FOR DATA SCIENCE

DSBE531

Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
1DSBE531CORPORATE FINANCE FOR DATA SCIENCE3+0+037,5

Course Details
Language of Instruction English
Level of Course Unit Master's Degree
Department / Program DATA SCIENCE
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course Introducing long term and short-term financing decision of businesses. Evaluating investment decisions to maximize the value of the firm. Introducing tools and techniques used in jobs in valuation, asset management, issue management, credit rating and analyst positions.
Course Content Following subjects are covered throughout the course: introduction to financial assets, investment decision rules, valuation of securities, portfolio selection theorem, and investment performance measurements. Therefore the course content covers the basics of risk management, financial derivatives and financial engineering. In addition, it is aimed to teach how to make financial decisions and express these decisions using various computer programs. Course content can be divided into three main parts: Investment decision making, security valuation, and risk and return.
Course Methods and Techniques
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Associate Prof.Dr. Adil ORAN adil.oran@agu.edu.tr
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources


Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
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ECTS Allocated Based on Student Workload
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Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Exemplify which main sources of finance a company has.
2 Recognize financial markets, institutions and instruments.
3 Analyze economic or financial data with data science methods.
4 Apply portfolio management and corporate finance analysis with data science.


Weekly Detailed Course Contents
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Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10
C1 4 5 5 3 5 4
C2 4 3 1 5 4
C3 5 5 5 5 5 5 4 3 5 5
C4 5 5 4 5 5 5 5 4 5 5

Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant


https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=76792&lang=en