This course introduces students to analyzing and employing machine learning algorithms to evaluate public policies. To that end, the student first becomes conversant with the core issues of causal statistics, such as the potential outcomes framework, drawing causal diagrams, and recognizing sufficient conditions for statistical identification. Simultaneously, the class touches on the building blocks of R, including data wrangling and functional programming. After acquiring basic knowledge of coding and causal statistics, the material gravitates around the building blocks of machine learning (ML) and their implementation in R. Subsequently, the student learns about the meaningful overlaps between causal statistics and ML by reviewing the notions of Causal Trees and Causal Forests. Finally, a significant portion of the course addresses a series of applications concerning evaluations of public initiatives, such as police reforms, environmental preservation, and educational programs.
Machine Learning for Policy Evaluation (ECON 495)
| Programs\Type | Required | Core Elective | Area Elective |
| Computer Science and Engineering | * | ||
| Computer Science and Engineering | * | ||
| Data Science and Analytics | * | ||
| Decision and Behavior Minor | * | ||
| Economics | * | ||
| Economics | * |
CONTENT
PROGRAMME OUTCOMES
1. Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others.
2. Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice.
3. Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects; have the ability to continue to educate him/herself.
4. Communicate effectively in Turkish and English by oral, written, graphical and technological means.
5. Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams.
1. Possess sufficient knowledge of mathematics, science and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems.
2. Identify, define, formulate and solve complex engineering problems; choose and apply suitable analysis and modeling methods for this purpose.
3. Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; possess knowledge of standards used in engineering applications; use information technologies effectively.
4. Have the ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose.
5. Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas.
6. Possess knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development.
7. Possess knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; knowledge of behavior according to ethical principles, understanding of professional and ethical responsibility.
8. Have the ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.
1. Design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs and to solve a computational problem.
2. Demonstrate knowledge of discrete mathematics and data structures.
3. Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering.
1. Provide constructive analysis of economic phenomena at the national and international level, and interactions between the two.
2. Develop an understanding of organizations and institutions in the society as well as their influence on the economy.
3. Recognize how incentives shape the behavior of individuals and organizations.
4. Identify "economic" problems and propose alternative models and/or design and conduct research to provide viable solutions using theoretical tools and/or quantitative methods.
5. Communicate problems and solutions to managerial and policy decision-making units as well as to lay audiences.