CHEME 5660

CHEME 5660

Course information provided by the 2025-2026 Catalog.

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.


Prerequisites REF-FA25/Corequisites REF-FA25 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. Corequisites: None.

Last 4 terms offered (None)

Outcomes REF-FA25

  • 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.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session. 

  • 3 Credits Stdnt Opt

  •  6333 CHEME 5660   LEC 001

    • TR
    • Aug 25 - Dec 8, 2025
    • Varner, J

  • Instruction Mode: In Person

Syllabi: none
  •   Regular Academic Session. 

  • 3 Credits Stdnt Opt

  • 10017 CHEME 5660   LEC 002

    • TR
    • Aug 25 - Dec 8, 2025
    • Varner, J

  • Instruction Mode: Distance Learning-Synchronous