ECON 449 Data Science with Economic Applications
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The objective of the course is to teach key concepts, methods, and applications of data science in Economics. These include various regression models and artificial intelligence methods such as Random Forest, Neural Networks and K-means clustering. Students will learn which model to use to address an Economics problem and how to build a machine learning model using Python to solve an Economics problem. First, examples of different data science applications in Economics will be introduced, followed by a detailed introduction to data science methods. Then, case studies covering data science applications in the real world will be discussed. These discussions will also involve guest speakers from the industry. Finally, students will have group projects where they will develop machine learning models, which will help them combine methods and practice.
Credit units: 3 ECTS Credit units: 5, Prerequisite:
CS 125 and ECON 301.
Spring Semester (Doğa Demirhan)
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