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Data Science (MS)

by | Nov 17, 2022 | 0 comments

Data Science (MS)

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Admission Requirements

Start terms: Fall or spring
Deadline: Rolling admissions
Admission requirements

  • Completed application

  • Bachelor’s degree from an accredited institution with a 3.0 GPA

  • Official transcripts from all post-secondary institutions

  • Personal statement

  • Resume/CV

  • GRE or GMAT scores optional

INTERNATIONAL APPLICANTS
need to meet additional criteria, such as submitting TOEFL/IELTS scores. See our international admissions page for more information

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Drew Together Scholarship

Grab a friend, colleague, or group interested in furthering their career and educational footprint. You’ll each receive a $1,000 scholarship when you enroll together in Drew’s graduate programs.

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Master's Programs

Doctoral Programs

Certificate Programs

CONTACT INFORMATION

Office of Graduate Admissions

36 Madison Avenue Madison, NJ

973-408-3111

[email protected]

Contact a specific staff member

CONTACT

Alex Rudniy

Associate Professor, Mathematics & Computer Science & Director of Data Science

Hall of Sciences 312

[email protected]

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Big data. Bigger ideas.

The digitization of information—social networks, business transactions, healthcare records, and more—has transformed the world, necessitating a demand for people who understand all of the big data being collected and who can take action to help individuals and corporations to become smarter, faster, and ultimately more effective.

Through Drew’s Master of Science and graduate certificate programs in Data Science, you will:

  • Learn how to obtain, prepare, and manage data from a wide variety of sources.
  • Gain mastery of data analytical, machine learning, and artificial intelligence techniques.
  • Leave with a portfolio of projects and work experience from real-world learning projects and internships.

Review the Program Requirements >

Announcement

We are pleased to launch a new concentration within our Data Science Program: Data Science Applications in High-Energy Physics. This addition reflects our commitment to expanding interdisciplinary training and preparing students for emerging research and career opportunities at the intersection of data science and fundamental physics.

LEARN More

“Drew’s Master of Science in Data Science pairs well with my passion for biology, and broadens the roles that I’m eligible for and the value I can bring to companies/ teams. It also enables me to apply for jobs with a better salary range and have a stronger chance at obtaining a work visa than I did with a BS, should I ever need to apply for it.”

Mehek Agrawal C’23, G’24

Programs

Master of Science (30-36 credits, one year full-time)

Foundational courses (6 credits)
Must be taken prior to enrolling in core courses. May be taken during the summer before the program starts.

  • Introductory Statistics (or equivalent)
  • Introduction to Programming (or equivalent)

Fall (12 credits)

  • Statistics Using R (3 credits)
  • Computational Thinking/Programming in Python (3 credits)
  • Applied Regression Analysis (3 credits)
  • Elective (3 credits)

Spring (12 credits)

  • Networks and Text Mining (3 credits)
  • Data Analytics Using SQL and Relational Databases (3 credits)
  • Statistical Machine Learning (3 credits)
  • Data Visualization and Communication (3 credits)

Summer (6 credits)

  • Data Science Internship (3 credits)
  • Capstone: Case studies in Data Science (3 credits)

VIEW COURSE REQUIREMENTS >

Master of Science (30-36 credits - two years part-time - fall start)

Foundational courses (6 credits)
Must be taken prior to enrolling in core courses. May be taken during the summer before the program starts.

  • Introductory Statistics (or equivalent)
  • Introduction to Programming (or equivalent)

Fall I (6 credits)

  • Statistics Using R (3 credits)
  • Computational Thinking/Programming in Python (3 credits)

Spring I (6 credits)

  • Networks and Text Mining (3 credits)
  • Data Analytics Using SQL and Relational Databases (3 credits)

Fall II (6 credits)

  • Applied Regression Analysis (3 credits)
  • Elective (3 credits)

Spring II (6 credits)

  • Statistical Machine Learning (3 credits)
  • Data Visualization and Communication (3 credits)

Summer (6 credits)

  • Data Science Internship (3 credits)
  • Capstone: Cases studies in Data Science (3 credits)

VIEW COURSE REQUIREMENTS >

Master of Science (30-36 credits - two years part-time - spring start)

Foundational courses (6 credits)
Must be taken prior to enrolling in core courses. May be taken during the summer before the program starts.

  • Introductory Statistics (or equivalent)
  • Introduction to Programming (or equivalent)

Spring I (6 credits)

  • Data Analytics Using SQL and Relational Databases (3 credits)
  • Data Visualization and Communication (3 credits)

Fall I (9 credits)

  • Statistics Using R (3 credits)
  • Computational Thinking/Programming in Python (3 credits)
  • Applied Regression Analysis (3 credits)

Spring II (6 credits)

  • Networks and Text Mining (3 credits)
  • Statistical Machine Learning (3 credits)

Summer (6 credits)

  • Data Science Internship (3 credits)
  • Capstone: Case studies in Data Science (3 credits)

Fall II (3 credits)

  • Elective (3 credits)

VIEW COURSE REQUIREMENTS >

Graduate Certificates (12 credits each)

Our graduate certificates enhance core skills required to draw information from data. You may choose from one of three emphases: Statistics, Data Science or Business Analytics. Or, design your own program in consultation with the program director. If you complete one of these certificate programs, you may apply the credits to the Master of Science in Data Science.

Prerequisites (6 credits)
Must be taken prior to enrolling in a Data Science certificate program. May be taken during the summer before the program starts.

  • Introductory Statistics (or equivalent)
  • Introduction to Programming (or equivalent)

Data Science Certificate: Statistics (12 credits)

  • Statistics Using R (3 credits)
  • Applied Regression Analysis (3 credits)
  • Computational Thinking/Programming in Python (3 credits)
  • Statistical Machine Learning (3 credits)

VIEW COURSE REQUIREMENTS >

Data Science Certificate: Data Science (12 credits)

  • Statistics Using R (3 credits)
  • Networks and Text Mining (3 credits)
  • Computational Thinking/Programming in Python (3 credits)
  • Data Analytics Using SQL and Relational Databases (3 credits)

VIEW COURSE REQUIREMENTS >

Data Science Certificate: Business Analytics (12 credits)

  • Statistics Using R (3 credits)
  • Applied Regression Analysis (3 credits)
  • Financial Quantitative Analysis (3 credits)
  • Computational Finance and Large Data Analysis (3 credits)

VIEW COURSE REQUIREMENTS >

Latest News

Outcomes

With the digital transformation of academia and the workforce, it is not surprising that data science and data analytics jobs are projected to grow at some of the fastest rates in the near future.*

Job title Average salary Projected five-year growth
Actuaries $142,300 22%
Computer and Information Research Scientists $134,260 20%
Computer and Information Systems Managers $205,120 15%
Data Scientists $134,140 34%
Database Architects $158,930 4%
Statisticians $122,370 8%

*Note: Salary data was retrieved from https://www.bls.gov/oes/2023/may/oes_nj.htm. Projected growth was obtained from https://www.bls.gov/ooh/.

CAREER OUTCOMES

Graduates of Drew’s Data Science program have secured a wide range of data science and data analytics positions across industries.

Position Company
Founder PA Capital LLC
Associate Data Analyst Evernorth Health Services
Associate Cybersecurity Analyst Unqork
Data Scientist Healthfirst
Client Engineering Data Scientist IBM
Data Engineer Mediatek
AMS Office – Operational Excellence Sanofi
Compliance Consultant Bank of China USA
Business Intelligence Developer American Financing
EHR Data Analyst KCare
Associate WB Games Boston
Data Scientist Climate Engine
Revenue Management Analyst Resia

“My experience in this master’s program has been nothing short of amazing. In one short year, I gained enough knowledge and skills to land a highly competitive internship.”

Tanner Euston C’19, G’23

BIG Data.

BIGGER Future.

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