The Data Science minor consists of seven courses (21 credit hours), blending foundational and applied courses. Students from any discipline with a background in basic calculus and programming are able to enroll.
The curriculum is designed to ensure a balance of theoretical knowledge and practical application.
The Minor in Data Science is open to all students except those majoring in Data Science or Business Intelligence and Data Analytics (BIDA) program. To complete the minor the student must achieve at least a 2.0 grade-point average in seven three-credit courses from the following list, one three-credit course from each category.
The lists will be updated by the minor advisory committee as needed.
Curriculum
Calculus (select one from the following):
- MA131 Calculus 1 (Course Equivalents: MA 125)
- MA181 Basic Calculus (Prereq. MA180 or MA120
Linear Algebra (select one from the following):
- MA239 Elementary Linear Algebra (Prereq. MA 131 or MA181, not open to Mathematics or Applied Math and Stats majors; not open to students who have taken or are taking MA 232 or MA 339)
- MA339 Applied Linear Algebra (Prereq. MA132; MA230/231 recommended but not required)
- MA232 Elementary Differential Equations (Prereq.MA132)
Probability and Statistics (select one from the following):
- STAT282 General Statistics
- STAT318 Biostatistics (Spring Term)
- STAT383 Probability and Statistics (Prereq. MA132)
- STAT389 Probability and Statistics with Multivariate Analysis (Prereq. MA230 or MA231. Students may not enroll in STAT389 if they have credit for STAT383) (Fall Term)
- BY314/514 Bioinformatics (Prereq. BY160 and BY214)
- IA530 Probability & Statistics for Analytics
Introductory Programming (select one from the following):
- CS141 Introduction to Computer Science I
- ES100 (cross-listed HP103) Introduction to Engineering Use of the Computer
- IS110 Intro to Business Intelligence and Data Analytics
- IS237 Intro to Application Development (Spring Term)
Introduction to Data Science (select one from the following):
- MA/DS241 Introduction to Data Science (Coreq. STAT282, or STAT383, or STAT318, or STAT389) (Fall Term)
- IS301 Applied Data Analytics (Prereq. IS110. Students may not receive credit for IS200 as well as IS301, offered Fall and Spring)
- IA640 Information Visualization (Spring Term)
Data Management (select one from the following):
- IS314 Database Design & Management
- CS460/EE468 Database Systems (Prereq. Programming experience in a high-level language) (Spring Term)
- IA510 Database Modeling, Design & Implementation
Select one course from the following:
- CS344 Algorithms and Data Structures (Prereq. CS142 or EE262 or EE363, and MA132) (Spring Term)
- CS/MA449 Computational Learning (Prereq. CS344 and CS345, or consent of the instructor)
- CS451 Artificial Intelligence (Prereq. CS344, CS250 and CS341 recommended)
- CS470 Deep Learning (Prereq. CS142, EE262, or EE361, and MA339)
- CS473 Computer Vision (Prereq. CS142 or EE262, and MA339)
- EE402 Machine Learning on Biomedical Signals (Prereq. MA132, EE321, and BR400 or instructor approval) (Odd Fall Term)
- IS400 Applied Machine Learning (Prereq. IS237 or CS141 or EE261) (Fall Term)
- IS415 Data Warehousing for Analytics (Prereq. IS314)
- ME419 Data Science Tools (Prereq. ME 401, given when needed)
- STAT385 Bayesian Data Analysis (Prereq. STAT383 or MA/STAT381, or by instructor consent)
- STAT386 Time Series (given when needed)
- A capstone/project-based course or application elective that the Minor Advisory Committee approves is also acceptable.
- Any of the following grad-level courses:
- CE/SC/EV 502 Applications in Geospatial Analytics, Science, and Engineering (Spring Term)
- IA605 Data Warehousing (Prerequisite: IA 510) (Fall Term)
- A628 Introduction to Big Data Architecture and Applications (Prereq. IA503, IA510, and IA626 or equivalents) (Summer Term)
- IA650 Data Mining (Prereq. IA530 or equivalent) (Summer Term)
- IA651 Applied Machine Learning (Prereq. IA530) (Spring Term)
- Note: Prerequisite courses are listed below for reference purposes:
- IA503 Introduction to Programming
- IA 510 - Database Modeling, Design & Implementation
- IA520 Optimization Methods for Analytics
- IA626 Big Data Processing and Cloud Services
Suggested Sample Programs Based on Majors
Below is a sample pathway to earn a Data Science Minor tailored to various majors. Courses in bold indicate additional requirements beyond the core courses of the student's major.
- MA131 Calculus I (Course Equivalents: MA 125)
- MA339 Applied Linear Algebra (Prereq. MA132; MA230/231 recommended but not required)
- STAT383/389 Probability and Statistics (Prereq. MA132)
- CS141 Introduction to Computer Science I
- MA/DS241 Introduction to Data Science (Coreq. STAT282, or STAT383, or STAT318, or STAT389) (Fall Term)
- IS314 Database Design & Management or CS460 Database Systems (Prereq. Programming experience in a high-level language) (Fall Term)
- STAT385 Bayesian Data Analysis or STAT386 Time Series (given when needed)
- MA131 Calculus I (Course Equivalents: MA 125)
- MA339 Applied Linear Algebra (Prereq. MA132; MA230/231 recommended but not required)
- STAT383 Probability and Statistics (Prereq. MA132)
- CS141 Introduction to Computer Science I
- MA/DS241 Introduction to Data Science (Coreq. STAT282, or STAT383, or STAT318, or STAT389) (Fall Term) or IS301 Applied Data Analytics (Prereq. IS110. Students may not receive credit for IS200 as well as IS301, offered Fall and Spring)
- CS460 Database Systems (Prereq. Programming experience in a high-level language) (Spring Term)
- MA131 Calculus I (Course Equivalents: MA 125)
- MA232 Elementary Differential Equations (Prereq.MA132)
- STAT383/389 Probability and Statistics (Prereq. MA132)
- ES110 Introduction to Engineering Use of the Computer
- MA/DS241 Introduction to Data Science (Coreq. STAT282, or STAT383, or STAT318, or STAT389) (Fall Term) or IS301 Applied Data Analytics (Prereq. IS110. Students may not receive credit for IS200 as well as IS301, offered Fall and Spring)
- IS314 Database Design & Management
- ME419 Data Science Tools or EE402 Machine Learning on Biomedical Signals
- MA131 Calculus I (Course Equivalents: MA 125)
- MA232 Elementary Differential Equations (Prereq.MA132)
- STAT383/389 Probability and Statistics (Prereq. MA132)
- ES110 Introduction to Engineering Use of the Computer
- MA/DS241 Introduction to Data Science (Coreq. STAT282, or STAT383, or STAT318, or STAT389) (Fall Term) or IS301 Applied Data Analytics (Prereq. IS110. Students may not receive credit for IS200 as well as IS301, offered Fall and Spring)
- IS314 Database Design & Management or CS460 Database Systems (Prereq. Programming experience in a high-level language) (Fall Term)
- EE402 Machine Learning on Biomedical Signals
- MA131 Calculus I (Course Equivalents: MA 125)
- MA232 Elementary Differential Equations (Prereq.MA132)
- STAT 383 Probability and Statistics (Prereq. MA132)
- IS110 Intro to Business Intelligence and Data Analytics or IS237 Intro to Application Development (Spring Term) or ES110 Introduction to Engineering Use of the Computer
- MA/DS241 Introduction to Data Science (Coreq. STAT282, or STAT383, or STAT318, or STAT389) (Fall Term)
- IS314 Database Design & Management
- MA131 Calculus I (Course Equivalents: MA 125)
- MA232 Elementary Differential Equations (Prereq.MA132)
- STAT383/389 Probability and Statistics (Prereq. MA132)
- IS110 Intro to Business Intelligence and Data Analytics
- MA/DS241 Introduction to Data Science (Coreq. STAT282, or STAT383, or STAT318, or STAT389) (Fall Term) or IS301 Applied Data Analytics (Prereq. IS110. Students may not receive credit for IS200 as well as IS301, offered Fall and Spring)
- IS314 Database Design & Management
- MA181 Basic Calculus (Prereq. MA180 or MA120)
- MA239 Elementary Linear Algebra (Prereq. MA 131 or MA181, Not open to Mathematics or Applied Math and Stats majors; not open to students who have taken or are taking MA 232 or MA 339)
- STAT282 General Statistics or STAT318 Biostatistics (Spring Term) or BY314/514 Bioinformatics (Prereq. BY160 and BY214)
- IS110 Intro to Business Intelligence and Data Analytics or IS237 Intro to Application Development (Spring Term)
- IS301 Applied Data Analytics (Prereq. IS110. Students may not receive credit for IS200 as well as IS301, offered Fall and Spring)
- IS314 Database Design & Management
- IS400 Applied Machine Learning (Prereq. IS237 or CS141 or EE261) (Fall Term)
Please Note:
- Students seeking Math Minor should take MA/DS241 instead of IS301.
- Students majoring in engineering are recommended to take ME or EE as their professional elective course.
- Students with good programming background are encouraged to take CS as their professional elective course.
- Students with good information systems background are recommended to take a grad-level IA course as their professional elective course.
- Students with good statistics background are recommended to take STAT385 or STAT386 as their professional elective course.