ECTS - Stochastic Processes for Data Science

Stochastic Processes for Data Science (ECON483) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Stochastic Processes for Data Science ECON483 3 0 0 3 6
Pre-requisite Course(s)
N/A
Course Language English
Course Type N/A
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery
Learning and Teaching Strategies .
Course Coordinator
Course Lecturer(s)
  • Specialist Bora Güngören
Course Assistants
Course Objectives The main contents are; essentials of stochastic integrals and stochastic differential equations. Probability distributions and heavy tails, ordering of risks, aggregate claim amount distributions, risk processes, renewal processes and random walks, markov chains, continuous Markov models, martingale techniques and Brownian motion, point processes, diffusion models, and applications in various subject related data science.
Course Learning Outcomes The students who succeeded in this course;
  • Upon the completion of this course, the student will be able to: 1. Define and analyze the data structure by using the mathematical tools;
  • 2. use mathematical models and solve for equilibrium.
Course Content Essentials of stochastic integrals and stochastic differential equations; probability distributions and heavy tails, ordering of risks, aggregate claim amount distributions, risk processes, renewal processes and random walks, Markov chains, continuous Markov models, Martingale techniques and Brownian motion, point processes, diffusion models, and applications in various subject related data science.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Stochastic integrals and Stochastic differential equations Lecture notes available
2 Probability distributions and heavy tails Lecture notes available
3 Ordering of risks Lecture notes available
4 Aggregate claim amount distributions Lecture notes available
5 Risk processes Lecture notes available
6 Renewal processes and random walks Lecture notes available
7 Midterm Exam
8 Markov chains Lecture notes available
9 Continuous Markov models Lecture notes available
10 Martingale techniques and Brownian motion. Lecture notes available
11 Point processes Lecture notes available
12 Difüzyon Modelleri Ders Notları
13 Asymptotic theory of nonstationary variables and Brownian Bridge Lecture notes available
14 Asymptotic theory of nonstationary variables and Brownian Bridge Lecture notes available
15 Density Functions Lecture notes available
16 Fİnal Exam

Sources

Other Sources 1. Ders Notları / Lecture notes available

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation 1 10
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation 2 20
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 20
Final Exam/Final Jury 1 50
Toplam 5 100
Percentage of Semester Work
Percentage of Final Work 100
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Acquiring the skills of understanding, explaining, and using the fundamental concepts and methods of economics X
2 Acquiring the skills of macro level economic analysis X
3 Acquiring the skills of micro level economic analysis X
4 Understanding the formulation and implementation of economic policies at the local, national, regional, and/or global level X
5 Learning different approaches on economic and related issues X
6 Acquiring the quantitative and/or qualitative techniques in economic analysis X
7 Improving the ability to use the modern software, hardware and/or technological devices X
8 Developing intra-disciplinary and inter-disciplinary team work skills X
9 Acquiring an open-minded behavior through encouraging critical analysis, discussions, and/or life-long learning X
10 Adopting work ethic and social responsibility X
11 Developing the skills of communication. X
12 Improving the ability to effectively implement the knowledge and skills in at least one of the following areas: economic policy, public policy, international economic relations, industrial relations, monetary and financial affairs. X

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 3 48
Presentation/Seminar Prepration 1 20 20
Project
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 10 10
Prepration of Final Exams/Final Jury 1 10 10
Total Workload 136