Applied Coding for Risk Management Seminar, Presented by the ERM Program

May 19 – July 21, 2023
Time for all workshops: 11:00 am – 12:30 pm ET

Coding is a powerful tool used everywhere. This Python based seminar series is intended to take your ability to model risk to the next level. The seminars cover business simulation, database queries on time series data, object oriented programming applied to games, analytics with Python, and intermediate Python.

How To Join a Session

Click here at 11:00 am ET on the day of your desired workshop to join virtually. Each workshop ends at 12:30 pm ET.

Workshop Info

Friday, May 19 | 11:00 am to 12:30 pm ET
OOP and Games 1
Object Oriented Programming is a powerful tool for collaborative work. The approach is used on large projects, 3rd party analytics platforms. And a great way to learn to code with objects is to build a game in Python! In part 1, we'll use PyGame to build objects and control them. In part 2, we'll make a game with those objects.

Friday, May 26 | 11:00 am to 12:30 pm ET
OOP and Games 2
Object Oriented Programming is a powerful tool for collaborative work. The approach is used on large projects, 3rd party analytics platforms. And a great way to learn to code with objects is to build a game in Python! In part 1, we'll use PyGame to build objects and control them. In part 2, we'll make a game with those objects.

Friday, June 2 | 11:00 am to 12:30 pm ET
OOP and Inheritance
After the hands-on experience building a game with Python, we can now study some of the theory behind Object Oriented Programming.

Friday, June 9 | 11:00 am to 12:30 pm ET
Time Series Data 1
Information is frequently organized across time. And this time series of data usually requires its own style of analytics and syntax. Come learn that syntax in Python. In part 1, we'll cover the foundational tools for modeling time series data. In part 2, we'll cover how to model volatility.

Friday, June 16 | 11:00 am to 12:30 pm ET
Time Series Data 2
Information is frequently organized across time. And this time series of data usually requires its own style of analytics and syntax. Come learn that syntax in Python. In part 1, we'll cover the foundational tools for modeling time series data. In part 2, we'll cover how to model volatility.

Friday, June 23 | 11:00 am to 12:30 pm ET
Analytics with Python
Sometimes you know the analytics but you don't know the code. And sometimes, the first step to learning the theory is running the code. For both these cases, we bring you this analytics presentation. Here you can learn the syntax for running statistics and machine learning analytics.

Friday, June 30 | 11:00 am to 12:30 pm ET
Monte Carlo Simulation
Some complex events can't be modeled with formulas but they can be simulated. Come join us to explore using Monte Carlo Simulation.

Friday, July 7 | 11:00 am to 12:30 pm ET
Intermediate Python 1
Come learn about list comprehensions, decorators, contexts, lamdba functions, map, filter, generators, args & kwargs, and much more!

Friday, July 14 | 11:00 am to 12:30 pm ET
Intermediate Python 2
Come learn about list comprehensions, decorators, contexts, lamdba functions, map, filter, generators, args & kwargs, and much more!

Friday, July 21 | 11:00 am to 12:30 pm ET
SQL and Time Series Data
Analyzing time series data requires management of timestamps and intervals, which can be challenging to handle with SQL. Come join us as we work through this challenge in the context of a loan portfolio.