FE520 Introduction to Python for Financial Applications

Course Catalog Description

Campus Fall Spring Summer
On Campus X X X
Web Campus X X X


Professor Email Office
Dan Wang
dwang35@stevens.edu Babbio Center 209
Zhiyuan Yao
zyao9@stevens.edu HFSL Research Room

More Information

Course Description

This course is designed for those students have no experience or limited experience on Python. This course will cover the basis syntax rules, modules, importing packages (Numpy, pandas), data visualization, and Intro for machine learning on Python. You will need to implement what you learn from this course to do a finance- related project. This course aims to get you familiar with Python language, and can finish a simple project with Python

Course Resources


Dive into Python, http://www.diveintopython.net

Python for Data Analysis, Wes McKinney, O'Reilly Media, 2012

Python for Everyone, https://www.py4e.com/

Additional References

Python 3 Object Oriented Programming, Dusty Phillips, Packt Publishing, 2010.

Python for Finance - Analyze Big Financial Data, Yves Hilpisch, O'Reilly Media, 2014


Grading Policies

  • Quizzes (Weekly): 70%
  • Final Project: 30% (Report +Presentation)
  • Bonus: 5%
  • Homework should be finished by yourself, Cheating is 0 tolerate misconduct in Stevens. You will share the score with everyone for first time cheating, and you will fail for second time. There are only two requirements for the project: (i) you must use Python, (ii) project must be finance-related. You are encouraged to use any online resources for your project. Please don't limit the scope within the few packages we will introduce in class. Your projects are encouraged to use as much tech skills as you can, and the grades will be evaluated by comparing with the best project.

Lecture Outline

Topic Reading
Week 1 Installing Python and IPython Notebook
Week 2 Basic Python Language I Homework 1
Week 3 Basic Python Language II
Week 4 Basic Python Language I Homework 2
Week 5 Intro to useful standard library
Week 6 NumPy Basics Homework 3
Week 7 Getting Started with pandas
Week 8 No Class due to Columbus Day
Week 9 Pandas II Homework 4
Week 10 Plotting and Visualization
Week 11 Time Series Homework 5
Week 12 Financial and Economic Data Applications
Week 13 Introduction to Machine Learning I Homework 6
Week 14 Introduction to Machine Learning II
Week 15 Final Presentation