Analytics, MPS (Arlington)

With the proliferation of data across all sectors of the global economy, there is an immediate need for individuals to be knowledgeable in how to harness this data for continuous analysis and study. This spectrum spans from commercial to nonprofit, from higher education to government, and is constantly expanding with new sectors as data mining becomes the standard for knowledge gathering in the digital age.

The Master of Professional Studies in Analytics helps to meet the demand from employers with a graduate program that provides students with an end-to-end analytics education through a core curriculum with integrated experiential learning opportunities. The program is designed to prepare students with a deep understanding of the mechanics of working with data (i.e., its collection, modeling, and structuring), along with the capacity to identify and communicate data-driven insights that ultimately influence decisions.

Not only will students graduate with a portfolio of work samples that demonstrate their range and depth of skill, they will be part of a larger network of analytics professionals who will serve now and in the future.

The program offers students opportunities to:

• Build portfolios of real-world projects demonstrating competency with key technologies, visualization and communication techniques, and the ability to translate information into recommended actions.
• Gain a core analytical skill set upon which to layer more specialized technical skill sets or industry-specific applications.
• Develop a relationship to industry leaders and peers to leverage the Northeastern University education long after the formal education ends.
• Choose from a host of flexible programming options—all of which share an industry-defined core curriculum and a required, credit-bearing experiential requirement.
• Anticipate and contribute to the future direction of data analytics.

Beginning with students admitted in the fall of 2026, all students pursuing on-ground master's degree programs must complete a university-level experiential learning requirement. This requirement may be fulfilled through the curriculum, co-op, or other work- or industry-integrated learning experiences.

Complete all courses and requirements listed below unless otherwise indicated.

Required Courses

Course List

Code	Title	Hours
ALY 6105	Introduction to Applied Statistics	3
ALY 6115	Foundations of Data Analytics	3
ALY 6125	Intermediate Analytics	3
ALY 6135	Introduction to Enterprise Analytics	3
ALY 6145	Communication and Visualization with Data	3
Restricted Electives
Complete at least 4 semester hours from the following:		4
ALY 6400	Integrated Experiential Learning
ALY 6410	Healthcare Analytics: From Data to Decisions
ALY 6420	Introduction to Queries
ALY 6430	Machine Learning Operations
ALY 6440	Text Analytics and Language Processing
ALY 6983	Topics
Capstone
ALY 6980	Capstone	3

Concentrations or Electives Option

A concentration is not required. Students may complete the electives option in lieu of a concentration.

• Applied Machine Intelligence
• Statistical Modeling
• Electives Option

Program Credit/GPA Requirements

34 total semester hours required
Minimum 3.000 GPA required

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 Applied Machine Intelligence Concentration

Course List

Code	Title	Hours
AAI 6600	Applied Artificial Intelligence	3
AAI 6620	Applied Natural Language Processing	3
AAI 6630	Applied Computer Vision	3
Complete 3 semester hours from the following:		3
AAI 6640	Applied Deep Learning
AAI 6650	Recommender System
AAI 6680	AI for Cybersecurity

Statistical Modeling Concentration

Course List

Code	Title	Hours
ALY 6600	Data Warehousing and Querying	3
ALY 6610	Data Mining Applications	3
ALY 6620	Big Data and Cloud Computing	3
ALY 6630	Programming for Data Science	3

Electives Option

Course List

Code	Title	Hours
Complete any College of Professional Studies courses unused in the program in lieu of a specified concentration to meet total program required semester hours		12

Optional Experiential Learning Opportunities

The College of Professional Studies encourages its students to incorporate optional experiential learning opportunities in their academic plans. 

Course List

Code	Title	Hours
Co-op
This option requires 1 additional semester hour of credit and tuition in addition to this program's required credit hours.
INT 6200	Experiential Project Preparation	1
COP 6945	Co-op Work Experience—Full Time	0
or COP 6946	Global Co-op Work Experience—Full Time
or COP 6954	Co-op Work Experience - Half-Time
Integrative Experiential Learning
This option substitutes for 3 semester hours of restricted elective credits in programs that require at least 3 semester hours of restricted elective credits. If the student has already completed the program's restricted electives or the program does not have an elective requirement, this option requires 3 additional hours of credit and tuition in addition to this program's required credit hours.
INT 6943	Integrative Experiential Learning	3