CHEME 5660
Last Updated
- Schedule of Classes - December 10, 2024 7:37PM EST
- Course Catalog - December 10, 2024 7:07PM EST
Classes
CHEME 5660
Course Description
Course information provided by the Courses of Study 2024-2025.
A quantitative finance course that enables scientists and engineers to make quantitative financial decisions in corporate and wealth management contexts. We'll use tools from engineering, statistics, artificial intelligence (AI), data science (DS), and machine learning (ML) to model, analyze, and ultimately optimize financial systems and financial decision-making. The material from this course can be applied to traditional economic and engineering fields while simultaneously providing a core set of tools for students interested in entrepreneurship or opportunities in the financial and consulting industries. Course assignments will be completed using LaTeX.
When Offered Fall.
Prerequisites/Corequisites Prerequisite: knowledge of programming languages, such as Python, Matlab, Julia and mathematical and computing topics, such as probability, statistics, optimization, and data science tools, such as Jupyter notebooks, DataFrames, etc.
Outcomes
- Analyze financial data sets using tools from artificial intelligence (AI), data science (DS), and machine learning (ML).
- Identify quantitative models of asset pricing and process performance using real-time and static financial data sets.
- Demonstrate mastery of quantitative decision-making and risk management approaches in the context of corporate finance and personal wealth management.
Regular Academic Session.
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Credits and Grading Basis
3 Credits Stdnt Opt(Letter or S/U grades)
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Class Number & Section Details
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Meeting Pattern
- TR Frank H T Rhodes Hall 253
- Aug 26 - Dec 9, 2024
Instructors
Varner, J
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Additional Information
Instruction Mode: In Person
Regular Academic Session.
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Credits and Grading Basis
3 Credits Stdnt Opt(Letter or S/U grades)
-
Class Number & Section Details
-
Meeting Pattern
- TR Online Meeting
- Aug 26 - Dec 9, 2024
Instructors
Varner, J
-
Additional Information
Instruction Mode: Distance Learning-Synchronous
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