03:00 PM to 04:15 PM TR
Angel Cabrera Global Center 1306B
View in the schedule of classes
Section Information for Fall 2023
The field of economics is becoming increasingly computational. This means if you want to be competitive in the job market you must learn how to think in terms of computational algorithms and be able to program these algorithms on a computer. In the first half of the course, we will complete two in-class projects, first on the modelling and elicitation of risk preferences, and second on sequential decision making and optimal search. Students will be expected to self-study the Python programming language concepts before class and then apply them in class to the two projects. The projects will also introduce students to the Python scientific programming stack, including NumPy, SymPy, Pandas, Matplotlib, and statsmodels. In the second half of the class students will be introduced to two topical areas. First, students will learn how to use the python library mTree to design, program, and run, agent- based simulations and human subject experiments. Second, students will learn how to develop, refine, and use, generative AI models, such as OpenAI’s GPT-4, as a research tool. Students will be graded on class contributions and a proposed research project using mTree, or a generative AI model.
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Credits: 3
Enrollment limited to students with a class of Advanced to Candidacy, Graduate or Non-Degree.
Enrollment is limited to Graduate level students.
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