Data Analytics

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, corporations and organizations become smarter, faster and ultimately more effective.

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

Learn how to obtain, prepare and manage data from a wide variety of sources.
Gain mastery of data analytical techniques.
Leave with a portfolio of projects and work experience from experiential learning projects and internships.

Drew’s Data Analytics programs are structured to focus on the intersections of statistics, computer science, skills and technologies. ”

Programs

Both our 12-credit certificate programs and our 30-36 credit Master of Science degree will prepare you to become an advanced analyst who can create and develop data sets and analytic protocols, communicate your analytic findings to leaders and general audiences and ultimately participate in data-informed decision making.

The examples for the course of studies below are for full-time programs, but part-time options are also available.

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

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)

Data Analytics: Introduction, History and Case Studies (3 credits)
Data Visualization and Communication (3 credits)
Applied Regression Analysis (3 credits)
Network and Text Mining (3 credits)

Spring (12 credits)

Modeling and Simulation (3 credits)
SQL for Big Data OR Computational Finance and Large Data Analysis (3 credits)
Statistical Machine Learning (3 credits)
Elective (3 credits)

Summer (6 credits)

Data Analytics Internship (3 credits)
Capstone: Case studies in Data Analytics (3 credits)

Master of Science (30-36 credits - two years full-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 (9 credits)

Data Analytics: Introduction, History and Case Studies (3 credits)
Data Visualization and Communication (3 credits)
Applied Regression Analysis (3 credits)

Spring I (9 credits)

Modeling and Simulation (3 credits)
SQL for Big Data (3 credits)
Statistical Machine Learning (3 credits)

Fall II (9 credits)

Network and Text Mining (3 credits)
Data Analytics Internship (3 credits)
Elective (3 credits)

Spring II (3 credits)

Capstone: Case Studies in Data Analytics (3 credits)

Master of Science (30-36 credits - two years full-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 (9 credits)

Modeling and Simulation (3 credits)
Statistical Machine Learning (3 credits)
Elective (3 credits)

Fall I (9 credits)

Data Analytics: Introduction, History, and Case Studies (3 credits)
Data Visualization and Communication (3 credits)
Applied Regression Analysis (3 credits)

Spring II (9 credits)

SQL for Big Data (3 credits)
Data Analytics Internship (3 credits)
Capstone: Case studies in Data Analytics (3 credits)

Fall II (3 credits)

Network and Text Mining (3 credits)

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 Analytics.

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

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

Data Analytics Certificate: Statistics (12 credits)

Data Analytics: Introduction, History and Case Studies (3 credits)
Applied Regression Analysis (3 credits)
Modeling and Simulation (3 credits)
Statistical Machine Learning (3 credits)

Data Analytics Certificate: Data Science (12 credits)

Data Analytics: Introduction, History and Case Studies (3 credits)
Network and Text Mining (3 credits)
Modeling and Simulation (3 credits)
SQL for Big Data (3 credits)

Data Analytics Certificate: Business Analytics (12 credits)

Data Analytics: Introduction, History and Case Studies (3 credits)
Applied Regression Analysis (3 credits)
Financial Quantitative Analysis (3 credits)
Computational Finance and Large Data Analysis (3 credits)

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
Analytics managers	$105,909	15%
Data scientists & advanced analysts	$94,576	28%
Data-driven decision makers	$91,467	14%
Data systems developers	$78,553	15%
Data analysts	$78,553	16%
Functional analysts	$69,162	17%

*Burning Glass Technologies

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Data Analytics

Data Analytics

Big data. Bigger ideas.

Programs

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

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

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

Graduate Certificates (12 credits each)

Outcomes

Admission information

Contact Information

Office of Graduate Admissions