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About the course
This course uses Python 3 via Anaconda Distribution. Participants must download and install the latest version of Anaconda Distribution: https://www.anaconda.com/download/ to work through the course. Anaconda comes with Python, Spyder text editor, Jupyter Notebook, and many popular libraries.
This course is geared for financial analysts, portfolio analysts, quantitative analysts, risk managers, or anyone who works with large financial datasets or complex models. No prior programming knowledge or experience is required.
This course is hands-on and participants are expected to follow along with the instruction. Financial applications will be used throughout the course to demonstrate the programming concepts.
Session #1 (3 hours)
Introduction to Python: Writing Code, Using Logic, and Creating Definite Loops Introduction to Python• Why do financial professionals use Python?
- Familiarizing yourself with Anaconda and the Spyder integrated development environment
- Writing simple code
- General syntax rules
- Commenting in the code
- Running Python from the command prompt
- Defining variables
- Variable types
- Reserved words
- Numeric and string operators
- Understanding syntax errors and debugging
- Incorporating inputs from the user
- Formatting your output
- Understanding Boolean Expressions
- Reviewing Comparison Operators
- Working with IF…ELIF…ELSE syntax
- Understanding the importance of indentation
- Using logic to prevent potential errors and build more robust code
Looping: Definite Loops
- Creating definite loops to repeat code
- Working with iteration and counter variables
- Creating and working with collections
- Writing recursive syntax within code
- Learning common practical uses of definite loops
Session #2 (3 hours) Introduction to Python: Creating Loops, Building Functions, and Working with Python Libraries
Looping: Indefinite Loops
- Understanding when to use and how to write indefinite loops
- Learning the dangers of indefinite loops
- Working with nested loops
- Understanding arguments, parameters, and results
- Defining functions to store values, call expressions, and return output efficiently
- Creating functions with multiple parameters
Importing/Creating and Using Libraries (packages or modules) in Python
- Importing Modules
- Using functions in Modules
- Creating your own Modules
- Working with popular financial Modules (Math, NumPy, SciPi, Pandas, MatPlotLib, and more)
Working with Large Datasets, Data Manipulation and System Interaction
- Learning how Python can work with other data sources (CSV, SQL, etc.)
- Using several popular libraries to analyze and visualize a large dataset
Cara Marshall, Ph.D. is the Director of the Risk Management Graduate Program at Queens College, within the City University of New York. She has been a professor of finance and risk management at Queens College since 2004. Dr. Marshall is also a highly regarded consultant who has trained employee...
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