Sampath Jayarathna, Graduate Program Director
Balša Terzić, Physics Concentration Coordinator
Physics Concentration
The purpose of this concentration is to provide students with a thorough understanding of the methods and technologies to handle big data and to instill physics problem-solving skills rooted in big data solutions. It prepares them to become professionals trained in advanced data analytics, with the ability to transform large streams of multiple data sources into understandable and actionable information for the purpose of making decisions. The coursework enables the students to achieve a comprehensive list of tasks including collecting, storing, processing, and analyzing data, reporting statistics and patterns, drawing conclusions and insights, and making actionable recommendations.
Admission
The requirements for admission to the Master of Science in Data Science and Analytics are as follows:
- A baccalaureate degree in computer science, electrical and/or computer engineering, mathematics, statistics, information system & technology, or a related field from a regionally-accredited institution or an equivalent institution outside the U.S.; students holding a bachelor's degree in an unrelated field will need competency in topics related to basic statistics and computer science.
- GRE scores with a 50% or better attainment on quantitative reasoning (or waiver)
- Current scores on the Test of English as a Foreign Language (TOEFL) of at least 230 on the computer-based TOEFL or 79 on the TOEFL iBT, or IELTS 6.5 overall.
Curriculum Requirements
The program requires 30 credit hours. The curriculum includes two concentrations: computational data analytics and, business intelligence and analytics. A capstone project is required.
Data Science & Analytics Core
Course List
Code |
Title |
Credit Hours |
| Introduction to Data Science and Analytics | |
| Data Analytics and Big Data | |
| Data Visualization | |
| Probability Models for Data Science and Analytics | |
| Statistical Tools for Data Science and Analytics | |
| Intermediate Quantum Mechanics | |
| Quantum Mechanics I |
| Classical Mechanics | |
| Classical Electrodynamics I | |
| |
| Introduction to Particle Accelerator Physics | |
| Special Topics in Accelerator Physics | |
| Experimental and Computational Techniques in Accelerator Physics | |
| Methods of Experimental Physics | |
| Introduction to Nuclear Particle Physics | |
| Introduction to Quantum Field Theory I | |
| Special Topics in Physics | |
| Special Topics in Physics | |
| Introductory Computational Physics | |
| Computational Physics |
| Classical Electrodynamics II | |
Total Credit Hours | 30 |