Course Details

Course Information

Semester	Course Unit Code	Course Unit Title	T+P+L	Credit	Number of ECTS Credits	Last Updated Date
1	BA521	CORPORATE FİNANCE FOR DATA SCİENCE	3+0+0	3	7,5	13.05.2025

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	Traditional in class lectures and real life applications and cases will be utilized.
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	-
Course Notes	Course materials will be provided throughout the semester

Course Category

Mathematics and Basic Sciences	%20
Social Sciences	%15
Field	%65

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

In-Term Studies	Quantity	Percentage
Yarıyıl İçi Çalışmalarının Başarı Notunun Katkısı	1	% 20
Quiz/Küçük Sınav	2	% 10
Ödev	3	% 15
Proje/Çizim	1	% 15
Sunum/Seminer	1	% 5
Final examination	1	% 35
Total	9	% 100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration	Total Work Load
Ev Ödevi	3	5	15
Sunum için Hazırlık	1	5	5
Teslim İçin Hazırlık	1	15	15
Sunum	1	3	3
Soru Çözümü	5	3	15
Proje	1	20	20
Kısa Sınav	2	2	4
Okuma	10	2	20
Kişisel Çalışma	10	5	50
Ders dışı çalışma	5	4	20
Yüz Yüze Ders	14	3	42
Derse Devam	14	1	14
Final Sınavı	1	2	2
Total Work Load			Number of ECTS Credits 7,5 225

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:

No	Learning 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

Week	Topics	Study Materials	Materials
1	Course Introduction and Basic Concepts	Review course objective & content	Syllabus
2	Structure and Meaning of Financial Statements	Review balance sheet, income statement	Lecture notes
3	Financial Ratio Analysis	Practice ratio calculations	Sample tables
4	Cash Flows and Free Cash Flow	Learn cash flow formulas	Textbook
5	Time Value of Money and NPV	Apply NPV calculations	Lecture notes
6	Capital Budgeting	Analyze investment projects	Case study
7	Risk and Return, Beta, Cost of Capital	Research risk indicators	Article + charts
8	Midterm Exam	General review of previous topics	-
9	Capital Structure and Leverage	Study capital structure decisions	Textbook
10	Dividend Policy	Compare dividend approaches	Reading material
11	Business Valuation Methods	Review DCF model	Lecture notes
12	Financial Forecasting and Planning	Prepare forecast models in Excel	Excel templates
13	Data-Driven Financial Decision Support	Work with financial datasets	Applied case
14	Course Review and Wrap-Up	Final exam review	Course summary, Q&A

Contribution of Learning Outcomes to Programme Outcomes

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

https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=75118&lang=en