BS in Data Science with Industrial Engineering Concentration

Degree Requirements

To earn a Bachelor of Science in Data Science with an Industrial Engineering Concentration from UIC, students need to complete university, college, and department degree requirements. The degree requirements are outlined below. Students should consult the College of Engineering section for additional degree requirements and college academic policies.

Summary of Requirements
General and Basic Education Requirements37
Core Courses57
Industrial Engineering Concentration Requirements13
Free Electives13
Total Hours120

General and Basic Education Requirements

ENGL 160Academic Writing I: Writing in Academic and Public Contexts3
ENGL 161Academic Writing II: Writing for Inquiry and Research3
Foreign Language a8
Understanding the Individual and Society course b3
Understanding U.S. Society course b3
Exploring World Cultures course b3
Understanding the Creative Arts course b3
Understanding the Past course b3
Two Analyzing the Natural World courses (with lab) b,c8
Total Hours37
a

Additional information on the COE's foreign language policy can be found in the College of Engineering section of the catalog.

b

Students should consult the General Education section of the catalog for a list of approved courses. 

c

Students planning to pursue the Bioinformatics Concentration will take BIOS 110 and BIOS 120 to fulfill the Analyzing the Natural World requirement.

Core Courses

Required Courses
ENGR 100Engineering Success Seminar (no graduation credit)1
MATH 180Calculus I4
MATH 181Calculus II4
MATH 210Calculus III3
MATH 310Applied Linear Algebra3
Select one of the following3
CS 111
Program Design I
CS 112
Program Design I in the Context of Biological Problems
CS 113
Program Design I in the Context of Law and Public Policy
CS 141Program Design II3
CS 151Mathematical Foundations of Computing3
or MCS 361 Discrete Mathematics
CS 211Programming Practicum3
CS 251Data Structures4
CS 377Ethical Issues in Computing3
Select one of the following:3
STAT 381
Applied Statistical Methods I
IE 342
Probability and Statistics for Engineers a
ECE 341
Probability and Random Processes for Engineers b
STAT 382Statistical Methods and Computing3
or IDS 462 Statistical Software for Business Applications
STAT 385Elementary Statistical Techniques for Machine Learning and Big Data3
STAT 481Applied Statistical Methods II3
IDS 312Business Project Management3
IDS 435Optimization for Analytics3
CS 418Introduction to Data Science c3
or IDS 472 Business Data Mining
CS 480Database Systems c3
or IDS 410 Business Database Technology
Total Hours57
a

IE 342 must be taken for the Concentration in Industrial Engineering.

b

ECE 341 must be taken for the Concentration in Data Processing, Science, and Engineering.

c

CS 418 and CS 480 must be taken for the Concentration in Computer Science.

Industrial Engineering Concentration Requirements

Required Courses
Note: IE 342 must be chosen as the selective in the Common Core in order to pursue this concentration.
IE 345Regression Applications and Forecasting in Engineering3
IE 365Work Productivity Analysis4
IE 446Advanced Quality Control and Reliability3
IE 471Operations Research I3
Optional Electives
IE 442
Design and Analysis of Experiments in Engineering
IE 461
Safety Engineering
IE 463
Manufacturing Facilities Design and Material Handling
IE 466
Production Operation Analytics and Inventory Control
IE 467
Discrete Event Computer Simulation Application
IE 472
Operations Research II
IE 473
Stochastic Processes and Queuing Models
Total Hours13

Free Electives

Electives
Select 13 hours of Free Electives.13
Total Hours13

Sample Course Schedule

Plan of Study Grid
First Year
First SemesterHours
CS 111
or CS 112
or CS 113
 Program Design I
or Program Design I in the Context of Biological Problems
or Program Design I in the Context of Law and Public Policy
 3
ENGL 160 Academic Writing I: Writing in Academic and Public Contexts 3
MATH 180 Calculus I 4
Analyzing the Natural World (with Lab) General Education course 4
ENGR 100 Engineering Success Seminar (no graduation credit) 1
 Hours14
Second Semester
CS 141 Program Design II 3
ENGL 161 Academic Writing II: Writing for Inquiry and Research 3
MATH 181 Calculus II 4
General Education Core course 3
Foreign Language 4
 Hours17
Second Year
First Semester
CS 151
or MCS 361
 Mathematical Foundations of Computing
or Discrete Mathematics
 3
CS 211 Programming Practicum 3
IE 342 Probability and Statistics for Engineers 3
Analyzing the Natural World (with lab) General Education course 4
Foreign Language 4
 Hours17
Second Semester
CS 251 Data Structures 4
STAT 382
or IDS 462
 Statistical Methods and Computing
or Statistical Software for Business Applications
 3
IDS 312 Business Project Management 3
MATH 210 Calculus III 3
General Education Core course 3
 Hours16
Third Year
First Semester
CS 377 Ethical Issues in Computing 3
CS 480
or IDS 410
 Database Systems
or Business Database Technology
 3
STAT 385 Elementary Statistical Techniques for Machine Learning and Big Data 3
MATH 310 Applied Linear Algebra 3
General Education Core course 3
 Hours15
Second Semester
CS 418
or IDS 472
 Introduction to Data Science
or Business Data Mining
 3
STAT 481 Applied Statistical Methods II 3
IDS 435 Optimization for Analytics 3
Concentration Requirement 3
Free Elective 3
 Hours15
Fourth Year
First Semester
Concentration Requirement 3
Concentration Requirement 3
General Education Core course 3
Free Elective 4
 Hours13
Second Semester
Concentration Requirement 3
Concentration Requirement 3
General Education Core course 3
Free Elective 4
 Hours13
 Total Hours120