Teaching Philosophy
I believe in creating an engaging and inclusive learning environment where complex economic concepts become accessible through practical applications and real-world examples. My teaching approach combines theoretical rigor with hands-on experience, encouraging students to develop both analytical thinking and practical skills.
Current Courses
Academic Year 2024-2025
📊 Advanced Econometrics
Graduate Level • Fall 2024 • Ankara University
Comprehensive coverage of advanced econometric techniques including time series analysis, panel data methods, and limited dependent variable models. Emphasis on practical applications using R and Python.
Topics Covered:
- GARCH and volatility modeling
- Vector Autoregression (VAR)
- Cointegration and error correction
- Panel data econometrics
- Bayesian econometrics
🤖 AI in Economics
Undergraduate Level • Spring 2025 • Ankara University
Introduction to artificial intelligence applications in economic analysis, covering machine learning fundamentals, economic forecasting, and automated decision-making systems.
Learning Outcomes:
- Understanding ML fundamentals
- Economic data preprocessing
- Predictive modeling techniques
- Model evaluation and validation
- Ethical AI considerations
Educational Resources
📚 Course Materials
Comprehensive lecture notes, problem sets, and practical exercises developed for econometrics and AI courses.
- • Econometrics Lab Exercises
- • Python/R Code Examples
- • Dataset Collections
- • Video Tutorials
💻 Software Training
Hands-on workshops on statistical software and programming languages commonly used in economic research.
- • R Programming for Economics
- • Python Data Analysis
- • EViews and Stata Workshops
- • LaTeX for Academic Writing
🎯 Student Projects
Supervised undergraduate and graduate research projects focusing on applied econometrics and AI applications.
- • Bachelor's Thesis Supervision
- • Master's Project Guidance
- • Research Methodology Training
- • Publication Support
Student Supervision
Current Supervisions
Master's Theses (3)
- • "Machine Learning in Credit Risk Assessment"
- • "Cryptocurrency Market Efficiency Analysis"
- • "Labor Market Dynamics in Turkey"
Bachelor's Theses (5)
- • Exchange rate volatility studies
- • Inflation forecasting models
- • Regional economic development
- • Financial market integration
- • Energy economics analysis
Teaching Approach & Methods
Core Teaching Principles
- • Practical applications and real-world examples
- • Customized materials tailored to student needs
- • Interactive exercises and hands-on learning
- • Focus on both theory and computational implementation
Student Support
- • Exam preparation and study strategies
- • Effective communication and mentorship
- • High student satisfaction through personalized attention
- • Continuous feedback and progress monitoring
Teaching Innovation & Development
🚀 Innovative Methods
- Flipped Classroom: Students engage with content before class, allowing for more interactive discussions
- Real-world Applications: Using current economic events and data in teaching examples
- Collaborative Learning: Group projects that simulate real research environments
- Technology Integration: Interactive visualizations and simulation tools
📈 Teaching Experience & Development
- Platform: Superprof tutoring platform
- Teaching Format: Individual and small group lessons
- Student Focus: University students and early-career professionals
- Continuous Improvement: High student satisfaction through effective communication and mentorship