ECON 491

Spring 2023 All Classes

All Classes

Topics in Econometrics

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Credit: 3 OR 4 hours.

Special topics applying advanced econometrics concepts. Students will use quantitative analysis and economic theories to answer economic questions and uncover relationships between variables across a variety of topics; instruction in statistical and computing techniques as needed.

3 undergraduate hours. 4 graduate hours. May be repeated if topics vary, repeatability for undergraduate students unlimited; for graduate students to a maximum of 8 credit hours. Prerequisite: ECON 203; ECON 302; and MATH 220/221 or Calculus I equivalent. See Class Schedule for other prerequisites as indicated depending on topic and content.

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ECON 491 class schedule data for spring 2023
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
74775	Lecture-Discussion	A3	2:00PM -3:20PM	TR	David Kinley Hall	Bilias, Y	Part of Term: 1 Date Range: 01/17/23-05/03/23 Credit: 3 hours Section Title: Applied Machine Learning: Econ Section Info: FIELD: Econometrics. DESCRIPTION for Applied Machine Learning, Econ: Students will gain exposure to a variety of machine learning approaches for supervised and unsupervised learning. Topics include regularized approaches like lasso and ridge regression, trees, boosting, support vector machines, cluster analysis, and predictive assessment using cross validation. Emphasis is given on applications with the use of a programming language like R or Python. RESTRICTION INFO: https://go.economics.illinois.edu/SpringRestrictions Restriction(s): Restricted to Economics or Econometrics & Quant Econ or Computer Science & Economics major(s) or minor(s).
74776	Lecture-Discussion	A4	2:00PM -3:20PM	TR	David Kinley Hall	Bilias, Y	Part of Term: 1 Date Range: 01/17/23-05/03/23 Special Approval: Departmental Approval Required Credit: 4 hours Section Title: Applied Machine Learning: Econ Section Info: To earn the 4th credit hour, contact the instructor for details on graduate-credit work. DESCRIPTION for Applied Machine Learning, Econ: Please see CRN 74775. RESTRICTION INFO: https://go.economics.illinois.edu/SpringRestrictions Restriction(s): Restricted to students in the Economics department. Restricted to Graduate - Urbana-Champaign.
74773	Lecture-Discussion	B3	12:30PM -1:50PM	TR	David Kinley Hall	Bilias, Y	Part of Term: 1 Date Range: 01/17/23-05/03/23 Credit: 3 hours Section Title: Applied Machine Learning: Econ Section Info: FIELD: Econometrics. DESCRIPTION for Applied Machine Learning, Econ: Students will gain exposure to a variety of machine learning approaches for supervised and unsupervised learning. Topics include regularized approaches like lasso and ridge regression, trees, boosting, support vector machines, cluster analysis, and predictive assessment using cross validation. Emphasis is given on applications with the use of a programming language like R or Python. RESTRICTION INFO: https://go.economics.illinois.edu/SpringRestrictions Restriction(s): Restricted to Economics or Econometrics & Quant Econ or Computer Science & Economics major(s) or minor(s).
74774	Lecture-Discussion	B4	12:30PM -1:50PM	TR	David Kinley Hall	Bilias, Y	Part of Term: 1 Date Range: 01/17/23-05/03/23 Special Approval: Departmental Approval Required Credit: 4 hours Section Title: Applied Machine Learning: Econ Section Info: To earn the 4th credit hour, contact the instructor for details on graduate-credit work. DESCRIPTION for Applied Machine Learning, Econ: Please see CRN 74773. RESTRICTION INFO: https://go.economics.illinois.edu/SpringRestrictions Restriction(s): Restricted to students in the Economics department. Restricted to Graduate - Urbana-Champaign.