Master’s In Analytics
Elevate your data career by pursuing the Master of Professional Studies in Analytics at Northeastern University. This industry-aligned program provides students with advanced expertise in data collection, modeling, interpretation, visualization, and strategic decision-making.
With a strong emphasis on real-world, experiential learning, graduates are well-equipped to succeed in the rapidly evolving analytics domain. The curriculum bridges technical foundations with business intelligence, ensuring students can transform insights into meaningful action.
- You can start the process for just 5000 rupees
- Post-study work visa for 2 years
- 90% Placement rate
Intakes
January 2026
Duration
24 months
Application Deadline
December
Fees
$45,775
Campus Location
Boston
- Northeastern is a global research university with a strong emphasis on experiential learning: integrating real-world industry projects and academic coursework.
- The MPS in Analytics is STEM-designated, enabling graduates to access extended work-opt opportunities (in U.S. context).
- Students become part of a large network of analytics professionals, alumni and industry partners — enhancing relational and career opportunities.
Our alumni work at top companies
You build a portfolio of real-world project work that demonstrates your range, depth, and applied analytics skills (technology, visualization, communication, translation into action). Northeastern University Academic
Flexible programming options (full-time, part-time) across multiple campuses and delivery modes, enabling you to tailor to your schedule. cps.northeastern.
Access to experiential learning credit-bearing elements, bridging classroom theory with industry practice. Northeastern University Academic
Positioned to meet high employer demand — across commercial, nonprofit, education and government sectors — for professionals able to harness, structure, model and interpret data. Northeastern University Academic
The MPS in Analytics is designed to provide end-to-end analytics education: from data collection, modeling and structuring, through to the identification and communication of data-driven insights influencing decision-making. Northeastern University Academic Catalog+1
The program is structured around a core curriculum, an experiential learning component, and a capstone. Students also choose from concentration tracks and electives to specialise their skillset.
Delivery format: Available in full-time and part-time modes. Entry terms include fall, spring and winter (depending on campus).
Duration: While officially 45 quarter-hours are required, typical completion for many students is in the range of 12–18 months (depending on entry, load, and schedule) for U.S. campus.
Benefits of this schedule:
Flexibility to balance work/professional commitments while studying.
The opportunity to engage with actual industry-sponsored projects, thereby strengthening job readiness.
The capstone and portfolio work mean you leave with tangible outcomes, not just coursework.
Note: Starting Fall 2026, Northeastern moves its graduate programs (including this one) from a quarter-based to a semester-based calendar – your advisor will ensure smooth transition.
Core curriculum plus experiential learning: students complete foundational courses, then experiential Integrated Learning, and finally a Capstone project.
Concentration tracks available (Applied Machine Intelligence, Evidence-Based Management, Statistical Modeling) allow customisation of the analytical skills path.
Electives across diverse areas (predictive analytics, data warehousing & SQL, leadership in analytics, risk management, Python & analytics systems, domain applications such as healthcare/pharma data) give breadth and depth.
Alumni and industry-leader relationships: students join a network and have opportunity to connect with data professionals and employers.
Portfolio development: Final deliverables include actual project work which can be shown to future employers
Students are required to complete a total of 45 quarter hours (for the Boston program) and maintain a minimum GPA of 3.000.
Note on prior experience: If a student lacks prior educational or professional experience with data and database structures, they must take the course ITC 6000 (Database Management Systems). If they don’t, they must take an extra elective to reach the 45 quarter hours.Although not all detailed admission criteria (such as bachelor’s degree, transcripts, English proficiency) are fully listed in the catalog extract, other sources indicate: a bachelor’s degree from an accredited institution is normally required; for international students, appropriate English proficiency (TOEFL/IELTS etc) may apply.
Application is typically rolling, but candidates are advised to apply early for desired start term.
Required Core Courses (All students)
ALY 6000 Introduction to Analytics (3 hours) Northeastern University Academic Catalog
ALY 6010 Probability Theory & Introductory Statistics (3 hours) Northeastern University Academic Catalog
ALY 6015 Intermediate Analytics (3 hours) Northeastern University Academic Catalog
ALY 6050 Introduction to Enterprise Analytics (3 hours) Northeastern University Academic Catalog
ALY 6070 Communication & Visualization for Data Analytics (3 hours) Northeastern University Academic Catalog
ITC 6000 Database Management Systems (3 hours) — required only for students without prior database experience. Northeastern University Academic Catalog
Experiential Courses
ALY 6080 Integrated Experiential Learning (3 hours) Northeastern University Academic Catalog
ALY 6980 Capstone (3 hours) Northeastern University Academic Catalog
Concentrations (choose one)
Applied Machine Intelligence
ALY 6040 Data Mining Applications (3 hours) Northeastern University Academic Catalog
ALY 6110 Data Management & Big Data (3 hours) Northeastern University Academic Catalog
EAI 6000 Fundamentals of Artificial Intelligence (3 hours) Northeastern University Academic Catalog
EAI 6010 Applications of Artificial Intelligence (3 hours) Northeastern University Academic Catalog
EAI 6020 AI System Technologies (3 hours) Northeastern University Academic Catalog
Evidence-Based Management
ALY 6040 Data Mining Applications (3 hours) Northeastern University Academic Catalog
ALY 6060 Decision Support & Business Intelligence (3 hours) Northeastern University Academic Catalog
ALY 6120 Leadership in Analytics (3 hours) Northeastern University Academic Catalog
ALY 6130 Risk Management for Analytics (3 hours) Northeastern University Academic Catalog
PJM 6005 Project Scope Management (3 hours) Northeastern University Academic Catalog
Statistical Modeling
ALY 6020 Predictive Analytics (3 hours) Northeastern University Academic Catalog
ALY 6030 Data Warehousing & SQL (3 hours) Northeastern University Academic Catalog
ALY 6040 Data Mining Applications (3 hours) Northeastern University Academic Catalog
ALY 6110 Data Management & Big Data (3 hours) Northeastern University Academic Catalog
ALY 6140 Python & Analytics Systems Technology (3 hours) Northeastern University Academic Catalog
Electives (examples)
ALY 6020 Predictive Analytics Northeastern University Academic Catalog
ALY 6030 Data Warehousing & SQL Northeastern University Academic Catalog
ALY 6060 Decision Support & Business Intelligence Northeastern University Academic Catalog
ALY 6110 Data Management & Big Data Northeastern University Academic Catalog
ALY 6120 Leadership in Analytics Northeastern University Academic Catalog
ALY 6130 Risk Management for Analytics Northeastern University Academic Catalog
ALY 6140 Python & Analytics Systems Technology Northeastern University Academic Catalog
ALY 6150 Healthcare/Pharmaceutical Data & Applications Northeastern University Academic Catalog
ALY 6983 Topics Northeastern University Academic Catalog
Courses drawn from other disciplines: CED 6230 Quantitative Methods, CMN 6005 Foundations of Professional Communication, EAI 6000 Fundamentals of AI, EAI 6010 Applications of AI, EAI 6020 AI System Technologies, EAI 6400 Data Governance & Responsible AI, etc.
The experiential course and capstone offer real-world project experience, often in collaboration with industry/organisational sponsors, which enhances employability and professional readiness. graduate.northeastern.edu+1
Career paths that graduates of this programme can typically pursue include: Data Analyst, Data Scientist, Business Intelligence Analyst, Analytics Consultant, Data Engineer, Risk & Forecasting Analyst, Machine Learning Engineer, Data Visualization Specialist, and more. Shiksha+1
The programme leverages Northeastern’s large employer partner network, helping students with professional connections, internships/co-ops and job placements.
While the catalog does not list individual faculty names in the excerpt, the programme emphasises that teaching and supervision are delivered by experienced scholar-practitioners and industry professionals, reflecting current analytics industry needs and trends. graduate.northeastern.
Faculty expertise spans analytics systems, business intelligence, AI & machine learning, data governance and leadership, enabling a blend of technical depth and strategic insight.
Application process
Our admissions close once the requisite number of students is enrolled in the upcoming cohort. Apply early to secure your place.
1. Apply Online
Fill out the online application form. No additional tests or prerequisites required.
2. Pre-Screening
Our program team will contact you to confirm your eligibility.
3. Application Assessment
If selected, you will be offered a seat in the upcoming cohort. Pay the fee to secure your seat
4. Join the program
Once accepted, you will receive an official offer letter with instructions on how to pay and join the program. Limited Seats Available
