Training the Street (TTS) will host a two-day financial modeling and Python programming workshop for Belk College of Business graduate and undergraduate students on Feb. 21-22, from 9 a.m. to 4:30 p.m. in the Friday 280 computer lab.

This workshop is a valuable opportunity for students to gain essential skills, with additional self-study materials on CoPilot, mergers and acquisitions, advanced financial modeling, and advanced Python provided for registered participants. Registration costs $25, and financial assistance is available. Apply for a fee waiver by 2/10/2025. Contact Alisha Aycoth with questions at aaycoth1@charlotte.edu.

SESSION OVERVIEW

Day 1: Financial Modeling

This session has been designed to develop Excel efficiency and financial modeling skills through actual hands-on construction of an abridged financial model. The  completed product is a model with 5 years of projections data. Through practical examples and annotated Excel guides, the lectures will discuss theories, approaches, and applications of financial modeling. The participants will have the opportunity to construct a model of their own to apply the lessons learned in the lectures. Personal one-on-one assistance will be available to answer questions and give guidance while the participants are constructing the model.

Day 2: Python

During this hands-on course, participants will gain the skills needed to develop Python programs to solve typical finance problems, cutting through the noise of generic “Data Science” courses. Participants will be introduced to best-practices
programming in Python to clean, analyze, and visualize financial data.

WHAT’S INCLUDED

Included in the attendance fee and as a supplement to the live course, students will receive access to our online Financial Modeling and Python courses. Students will have the ability to review the content at any time and on any device.

PREREQUISITES

A general understanding of programming principles is recommended but not required. Participants should also understand finance concepts, but in-depth analytical understanding is not necessary. Participants are expected to download & install Anaconda or an equivalent Python distribution in advance of the course.