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Engineering Online

ISE 535 Python for ISE

3 Credit Hours

This is an intermediate course on the Python programming language. The objectives of the course are to reinforce procedural programming fundamentals, introduce object-oriented programming concepts for complex coding tasks, and to demonstrate usage of these core computing skills to perform common tasks encountered by industrial engineers. You will learn how to conduct File I/O operations, code and deploy core numerical and scientific computing subroutines within Python, and utilize the object-oriented paradigm to streamline your programs. Along the way, the course will expose you to some of Python’s most popular packages for data-intensive analysis – Numpy, SciPy, Matplotlib, and Pandas. Several practical examples from industrial engineering and other quantitative disciplines will be used to contextualize the introduced concepts. 

Prerequisites

A prior basic course in Python programming (ISE 135, DSC 201, or equivalent), a prior course in linear programming or basic optimization modeling (ISE 361), and a prior course on basic probability and statistics (ISE 370, ST 308, or ECE 209). Restrictive Statement: Department Approval Required.

Course Learning Outcomes

  • Understand the high-level components and semantics of the Python programming language.
  • Understand the capabilities and limitations of Python’s basic variable types and container types.
  • Write efficient Python subroutines for performing general-purpose tasks including input/output operations and data collection.
  • Demonstrate ability to leverage Python’s extensive libraries to handle, clean, analyze, and visualize data.
  • Effectively utilize Numpy, SciPy, Pandas, and other Python libraries to perform various tasks relevant to the field of industrial engineering.
  • Implement Python functions and classes to streamline code and to program using the object-oriented paradigm.

Course Requirements

Grading Components:

Midterms 40%
Quizzes 15%
Class Project 25%
 Final 20%

Required Textbook

C. Fuhrer, J. E. Solem, and O. Verdier, Scientific Computing with Python: High-performance

Scientific Computing with NumPy, SciPy, and Pandas, Packt Publishing Ltd, 2021. ISBN: 978-1-838-82232-3.

Updated 08/19/2024