The Data Science and Engineering Data Science major provides students with the knowledge and skills throughout the data science lifecycle. It covers the topics of data structure, discrete systems, algorithms and complexity, database systems, data ethics, big data analytics, and machine learning. Students will learn advanced data science courses with applications in various scientific and engineering domains. They will be able to apply what they learn to many data science application areas including manufacturing, pharmaceutical science, biomedical engineering, aerospace, and chemical and material engineering, and many other emerging areas.
Data Science and Engineering majors are required to complete the following Computer Science and Engineering (CSE) courses:
Course List
| Course |
Title |
Credits |
| CSE 1010 | Introduction to Computing for Engineers | 3 |
| CSE 2050 | Data Structures and Object-Oriented Design | 3 |
| CSE 2500 | Introduction to Discrete Systems | 3 |
| CSE 2600 | Introduction to Data Science and Engineering | 3 |
| CSE 3000 | Contemporary Issues in Computer Science and Engineering | 1 |
| CSE 3140 | Cybersecurity Lab | 2 |
| CSE 3500 | Algorithms and Complexity | 3 |
| CSE 4502 | Big Data Analytics | 3 |
| CSE 4701 | Principles of Databases | 3 |
| CSE 4820 | Introduction to Machine Learning | 3 |
| CSE 4939W | Computer Science and Engineering Design Project I | 3 |
| CSE 4940 | Computer Science and Engineering Design Project II | 3 |
All Data Science and Engineering majors must also complete the following:
Course List
| Course |
Title |
Credits |
| MATH 2110Q | Multivariable Calculus | 4 |
| MATH 2210Q | Applied Linear Algebra | 3 |
| |
| Probability | |
| Statistical Methods | |
| Probability Models for Engineers | |
| Introduction to Mathematical Statistics I | |
| |
| CHEM 1127Q | General Chemistry I | 4 |
| General Chemistry II | |
| CHEM 1137Q | Enhanced General Chemistry I | 4 |
| Enhanced General Chemistry II | |
| CHEM 1147Q | Honors General Chemistry I | 4 |
| Honors General Chemistry II | |
| PHYS 1401Q | General Physics with Calculus I | 4 |
| General Physics with Calculus II | |
| PHYS 1501Q | Physics for Engineers I | 4 |
| Physics for Engineers II | |
| PHYS 1601Q | Fundamentals of Physics I | 4 |
| Fundamentals of Physics II | |
| |
| BIOL 1107 | Principles of Biology I | 4 |
| BIOL 1108 | Principles of Biology II | 4 |
| BIOL 1110 | Introduction to Botany | 4 |
| CHEM 1127Q | General Chemistry I | 4 |
| CHEM 1128Q | General Chemistry II | 4 |
| PHYS 1401Q | General Physics with Calculus I | 4 |
| PHYS 1402Q | General Physics with Calculus II | 4 |
| PHYS 1502Q | Physics for Engineers II | 4 |
| PHYS 1601Q | Fundamentals of Physics I | 4 |
| PHYS 1602Q | Fundamentals of Physics II | 4 |
| ERTH 1050 | Earth's Dynamic Environment | 4 |
| or ERTH 1051 | Earth's Dynamic Environment (Lecture) |
| Earth's Dynamic Environment (Laboratory) | |
| |
| CSE 2102 | Introduction to Software Engineering | 3 |
| CSE 3250 | Introduction to Cloud Computing | 3 |
| CSE 3400 | Introduction to Computer and Network Security | 3 |
| or CSE 5850 | Introduction to Cyber-Security |
| CSE 3800 | Bioinformatics | 3 |
| or CSE 5800 | Bioinformatics |
| CSE 3802 | Numerical Methods in Scientific Computation | 3 |
| or ECE 3431 | Numerical Methods in Scientific Computation |
| CSE 4705 | Artificial Intelligence | 3 |
| CSE 4830 | Computer Vision and Machine Learning for Image Analysis | 3 |
| CSE 5520 | Data Visualization and Communication | 3 |
| CSE 5713 | Data Mining | 3 |
| CSE 5820 | Machine Learning | 3 |
| BME 4810 | Machine Learning Methods for Biomedical Signal Analysis | 3 |
| ECE 4131 | Introduction to Digital Signal Processing | 3 |
| ECE 4132 | Image Processing Systems Laboratory | 3 |
| STAT 3965 | Elementary Stochastic Processes | 3 |
| or MATH 3170 | Elementary Stochastic Processes |
Students select additional elective courses to reach a minimum of 120 credits.
