BS in Data Science with Industrial Engineering Concentration

Program Overview

The BS in Data Science with Industrial Engineering Concentration at UIC combines data science and industrial engineering, equipping students with skills to analyze and solve complex problems in various industries. The program emphasizes data analysis, modeling, optimization, and engineering principles, preparing graduates for careers in data-driven decision making, process improvement, and system design. Students complete coursework in core data science and industrial engineering, along with a concentration in industrial engineering, and have access to state-of-the-art facilities and resources.

Program Outline

BS in Data Science with Industrial Engineering Concentration at UIC

Degree Overview:

This program combines data science and industrial engineering, providing students with the skills to analyze and solve complex problems in various industries. The curriculum focuses on developing expertise in data analysis, modeling, optimization, and engineering principles. Graduates are prepared for careers in data-driven decision making, process improvement, and system design.

Objectives:

• Equip students with the knowledge and skills to apply data science techniques to real-world industrial engineering problems.
• Develop a strong foundation in industrial engineering principles, including optimization, simulation, and quality control.
• Prepare graduates for successful careers in various industries, including manufacturing, healthcare, finance, and technology.

Outline:

Coursework:

• Core Data Science Courses: These courses cover fundamental concepts in data analysis, machine learning, and statistical modeling.
• Core Industrial Engineering Courses: These courses provide a foundation in industrial engineering principles, including optimization, simulation, and quality control.
• Concentration Requirements: Students complete four courses in industrial engineering, focusing on specific areas like regression analysis, forecasting, work analysis, and operations research.
• Free Electives: Students can choose from a variety of courses to tailor their program to their interests and career goals.

Sample Course Schedule:

The program can be completed in four years, with a typical course schedule as follows:

• First Year: Focuses on foundational courses in mathematics, computer science, and engineering.
• Second Year: Introduces students to data science and industrial engineering concepts.
• Third Year: Deepens knowledge in data science and industrial engineering, with a focus on applications.
• Fourth Year: Concentrates on advanced topics and capstone projects.

Assessment:

• Coursework: Assignments, exams, and projects are used to assess student understanding of the material.
• Capstone Project: Students complete a real-world project that applies their knowledge and skills to solve an industrial engineering problem.

Teaching:

• The program utilizes a variety of teaching methods, including lectures, discussions, hands-on labs, and group projects.
• Faculty members are experts in data science and industrial engineering, with extensive industry experience.
• The program emphasizes active learning and encourages students to apply theoretical concepts to practical problems.

Careers:

Graduates of this program are prepared for careers in various industries, including:

• Manufacturing: Data analyst, process engineer, quality engineer
• Healthcare: Data scientist, operations analyst, healthcare consultant
• Finance: Financial analyst, risk analyst, quantitative analyst
• Technology: Data engineer, software engineer, data scientist

Other:

• The program is offered by the Department of Mechanical and Industrial Engineering within the College of Engineering.
• The program offers opportunities for internships and research experiences.
• The General Education requirements are listed in the context.
• The program requires a total of 120 credit hours.