IENG 331

Computer Applications in Industrial Engineering

College Course
Data Analysis
Python
Polars
Plotly
uv
Quarto
Spring 2025
Introduction to computer applications in industrial engineering: emphasis on system design and analysis and the role of computers in productivity improvement.
Author
Affiliation

Mr. Ozan Ozbeker

Industrial and Management Systems Engineering

Course Website

https://wvu-ieng-331.github.io

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 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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