DATA ANALYTICS FOR FINANCE
With a hands-on approach, covers advanced analytics methods for forecasting, predicting, reporting, and analyzing. Relies on Python as its primary coding language. Begins with a review of coding fundamentals and progressively delves into increasingly realistic and complex finance applications.
Prerequisites & course information
Requisites: ECON/FINANCE 300 Course Designation: Core GenEd - Mathematics & Quantitative Reasoning Repeatable for Credit: No Last Taught: Spring 2022 Learning Outcomes: 1. Understand the fundamentals of programming and how those fundamentals are implemented in Python Audience: Undergraduate 2. Download, organize, and manipulate data to prepare them for Finance applications Audience: Undergraduate 3. Visualize and organize Financial Data for the purpose of creating effective presentations Audience: Undergraduate 4. Apply these programming skills in the context of standard financial applications such as asset pricing model estimation, Monte Carlo simulations for capital budgeting purposes, portfolio optimization, and financial analysis and forecasting Audience: Undergraduate Learning Outcomes: 1. Understand the fundamentals of programming and how those fundamentals are implemented in Python Audience: Undergraduate 2. Download, organize, and manipulate data to prepare them for Finance applications Audience: Undergraduate 3. Visualize and organize Financial Data for the purpose of creating effective presentations Audience: Undergraduate 4. Apply these programming skills in the context of standard financial applications such as asset pricing model estimation, Monte Carlo simulations for capital budgeting purposes, portfolio optimization, and financial analysis and forecasting Audience: Undergraduate
Sources
- Course catalogue ↗2026-2027