IENG 331: Computer Applications in Industrial Engineering

Spring 2025

Course Info

WVU Catalog: Introduction to computer applications in industrial engineering: emphasis on system design and analysis and the role of computers in productivity improvement.

Prerequisite Course(s): ENGR 102 - Engineering Problem Solving 2

Class Meets: Tuesday/Thursday 11:00 AM - 12:15 PM

Class Location: Engineering Sciences Building (ESB) | Room G87B

Instructor: Ozan Ozbeker ()

Teaching Assistants: None

Important

All emails related to the course must have the following subject format:

{Course} - {Term} - {WVU MIX ID} - {Concise Question}

For example: IENG 331 - Spring 2025 - oo0006 - Question about XYZ. You can put more details in the email body.

Course Description

This course introduces Industrial Engineering students to the practical application of Python, SQL, and Excel for data analysis, process automation, and visualization, emphasizing real-world relevance and hands-on learning. Through projects and assignments, students will acquire skills to automate workflows, analyze datasets, and create effective data-driven solutions. The curriculum is designed to align with industry needs, fostering technical proficiency and communication skills for future engineering challenges​.

Learning Objectives

Upon successful completion of this course, students will be able to:

  1. Implement Python Programming Skills: Master the fundamentals of computer programming using Python, with a focus on industrial engineering applications.
  2. Recognize and Utilize Data Structures: Identify common data structures and their practical applications in solving engineering problems.
  3. Automate Analytical Workflows: Develop, debug, and refine programs to automate data processing and analytical operations.
  4. Leverage Data Libraries: Apply specialized Python libraries for data cleaning, manipulation, visualization, and analysis, streamlining complex workflows.
  5. Integrate with Databases: Connect to, query, design, and manage external datasets using tools like SQL and relevant Python libraries.
  6. Visualize and Communicate Insights: Create effective data visualizations to communicate findings to technical and non-technical audiences, aligning with industry expectations.
  7. Collaborate and Utilize Version Control: Utilize Git and GitHub for collaboration, version control, and portfolio building, fostering professional software engineering practices.
  8. Engage with Real-World Data: Develop proficiency in handling diverse, real-world datasets through hands-on projects, preparing for industry or academic pursuits.

These objectives are designed to align with ABET-defined Student Outcomes, fostering critical skills in problem-solving, communication, teamwork, and lifelong learning. Additionally, they emphasize practical relevance, ensuring students are prepared for dynamic roles in industrial engineering and beyond.

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