Masters Degree in Data Science
Memphis, USA
DURATION
2 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
Request application deadline *
EARLIEST START DATE
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TUITION FEES
USD 981 / per credit **
STUDY FORMAT
On-Campus
* international: March 1; domestic May 1
** Per credit hour, for international students. 798 USD: non-resident fee. 597 USD: resident fee
Scholarships
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Introduction
Discover Your Future in Data Science
Big data has revolutionized the way organizations make strategic decisions. Companies, non-profits, and government agencies expect their employees to be able to analyze data and effectively communicate their findings for decision making. As a result, workforce demand for individuals with science data skills is booming.
In response to the growing demand for data-savvy professionals, the University of Memphis is offering a new, STEM-designated MS in Data Science. Throughout this program, students will learn how to use advanced computational and statistical methods and tools to collect, store, retrieve, manipulate, interpret, and visualize data. Importantly, these methods and tools will be offered in the context of particular high-demand business and scientific disciplines, so graduates have the understanding and acumen to translate their findings into actions.
Data Science is one of the most highly sought-after and versatile degrees available. Graduates will be prepared to pursue careers in a wide range of organizations in business, government, biomedical, education, engineering, and applied sciences.
What is Data Science?
"The coming century is surely the century of data" (Donoho, 2000). Data Science is emerging as a new, transformative paradigm in science and technology. With large volumes of data being generated every day from multiple sources (including business data, biomedical data, educational data, science data, engineering data, and personal data), the importance of systematic and rigorous approaches to understanding and putting these large volumes of data to good use is now well recognized. With this explosion of data, there is a significant demand for experts in the industry, government, education, healthcare, etc., that have the requisite skills to collect, process, and analyze data. Indeed, demand for Data Science master's degrees has exploded in the last couple of years as indicated by the fact that the number of master's degrees awarded in this area has quadrupled from around 5,000 to around 20,000 between 2016 and 2018. Furthermore, Data Scientist has been consistently ranked as the most promising job (defined by high salary, high demand, continual growth, and potential for advancement) by major job search websites such as Glassdoor.
Reference: Donoho, D.L. (2000). High-Dimensional Data Analysis: The Curses and Blessings of Dimensionality. Lecture Delivered at the "Mathematical Challenges of the 21st Century" Conference of the American Math. Society, Los Angeles.
About the Program
The Master's degree in Data Science offers interdisciplinary training in the area of Data Science in order to meet booming demand in the job market. Indeed, the importance of systematic and rigorous approaches to understand and take advantage of large and diverse volumes of data is well recognized. Furthermore, Data Scientist has been consistently ranked as the most promising job (defined by high salary, high demand, continual growth, and potential for advancement) by major job search websites such as Glassdoor.
The nature of the program includes core courses in theoretical foundations of Data Science, i.e., Computer Science and Statistics, and elective courses in discipline-specific quantitative analysis methods. The elective courses are clustered in specific disciplines such as Economics or Biomedical. Students attending the program will acquire a wide range of Data Science competencies including (1) basic system administration, programming, and computational data processing, (2) basic mathematical and statistical concepts for data analysis, (3) advanced computational statistical and machine learning skills for big data analysis, (4) ethical aspects, security, reproducibility /provenance aspects of Data Science, and (5) Data Science problem solving conceptual model and process (meta-competencies).
Assistantships
Teaching and research assistantships are available for qualified applicants. These assistantships include a tuition waiver and a monthly living stipend.
Research Opportunities
Research, internship, and job opportunities in Data Science are numerous due to the importance of Data Science in today's world.
For instance, for the third year in a row, Data Scientist topped Glassdoor's list as the best job in America." Data scientist has ruled as one of the hottest jobs for years, proven by its third consecutive No. 1 ranking," according to Glassdoor Chief Economist Dr. Andrew Chamberlain. "This is due to the high demand (4,524 open jobs), the high salary ($110,000 median base salary), and high job satisfaction (4.2/5). Not only are tech companies scrambling to hire data scientists, but industries across the board, from health care to nonprofits to retail, are also searching for this talent."
For the Memphis area, Glassdoor indicates an average salary of $111,782 for Data Scientists.
Indeed, data and Data Science is having a broad impact and has huge potential to further impact products, services, and processes in all areas of our lives including business, government, nonprofits, and spanning all fields such as biomedical, education, science, engineering, and social and personal lives.
The UofM offers research opportunities in Data Science through individual projects as well as through the Data Science Research Cluster which provides leadership for the Data Science Research at the UofM and the local community by creating a vibrant research environment and training future data scientists to build a Data Science community of practice that includes academia, government and industry in West Tennessee, the Mid-South and beyond.
Assistantships
Teaching and research assistantships are available for qualified applicants.
Curriculum
Academic Program Requirements
The Master of Science degree in Data Science requires completion of 33 semester credit hours as follows: 15 credits from the core courses (see below), 15 credits from the list of electives (with the recommendation that 9 credits must be from a cluster or concentration area – see below), and 3 credits for a Master's project. A Master's Thesis option (6 credits) is also available in which case only 12 credits are needed from the list of electives. Alternatively, students may opt for a Capstone Project course (3 credits) as a way to meet the comprehensive examination requirement of the Graduate School for students who do not write a thesis. Students may choose an Independent Study (3 credits) if they opt for a Master's project or the Capstone Project course, in which case only 12 credits are needed from the list of electives.
Core Courses
- COMP 7/8150 - Fundamentals of Data Science (Computational aspects of Data Science)
- COMP 7115 - Database Systems
- COMP 7/8745 - Machine Learning
- MATH 7/8785 – Advanced Statistical Learning I
- MATH 7/8786 – Advanced Statistical Learning II
List of Electives (students are encouraged to pick at least 3 electives from a cluster or concentration area)
Core Data Science Cluster (Cluster 1)
- COMP 7/8116 - Advanced Database Systems
- COMP 7/8118 - Data Mining
- COMP 7/8130 - Information Retrieval/Web Search
- COMP 7/8740 - Neural Networks
- COMP 7/8747 - Advanced Topics in Machine Learning
- COMP 7/8780 - Natural Language Processing
- MATH 7/8670 - Applied Stochastic Models
- MATH 7/8680 - Bayesian Inference
- MATH 7/8657 Multivariate Statistics
- MATH 7647 Nonparametric Statistics
- MATH 7/8660 Applied Time Series Analysis
- MATH 7/8685 - Simulation & Computing
- MATH 7/8695 - Bootstrap/Other Methods
- MATH 7/8759 - Categorical Analysis
- ESCI 6515 Geographic Information Science
Biomedical Cluster (Cluster 2)
- BIOL 6490: Introduction to Genomics and Bioinformatics
- BIOL 7/8708: Data Science for Biologists
- COMP 7/8295: Algorithms in Computational Biology and Bioinformatics
- PUBH 7/8104 Large Data Sets
- PUBH 7/8205: Special Topics, Mining Data
- PUBH 7/8153: Biostatistics in Bioinformatics
- PUBH7/8150: Biostatistical Methods I
- PUBH7/8152: Biostatistical Methods II
- PSYCH 7302/8302: Advanced Statistics for Psychology I
Economics Cluster (Cluster 3)
- ECON 7810/8810: Econometrics I (Fundamentals of Econometrics)
- ECON 7811/8811: Econometrics II (Panel and limited dependent variable methods, inter alia)
- ECON 8812: Econometrics III (Times Series Analysis)
Business Information Technology Cluster (Cluster 4)
- MIS 7660 Advanced Data Management
- MIS 7621 Business Machine Learning II
- MIS 7720 Business Artificial Intelligence
- MIS 7710 Web Analytics
Gallery
Career Opportunities
Career Opportunities
Many reports regarding the job market state that there will be roughly four to five million jobs in the U.S. requiring data analysis skills.
Popular Careers
- Applications Architect
- Business Intelligence (BI) Developer
- Econometrician
- Forecasting
- Data Analyst
- Data Architect
- Data Engineer
- Data Scientist
- Machine Learning Engineer
- Machine Learning Scientist
National Companies Hiring Data Scientists
- Amazon
- Apple
- First Horizon
- IBM
- Intel
- Walmart
Memphis-based Companies Hiring Data Scientists
- FedEx
- St. Jude Children’s Research Hospital
- International Paper
- AutoZone
- Thomas & Betts
- Smith & Nephew
English Language Requirements
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