Analytics & Data Sciences Curriculum

Note: Applicants interested in this concentration will apply to our general Analytics track in the graduate admissions portal. Once admitted, students will use the suggested pathways below to customize their course plans in accordance to their educational/professional background and aspiring career goals.

Analytics Pathways

To assist students coming in with experiences in science or business areas, we have created pathways within the Analytics concentration to build on the student’s existing skills. All Analytics students must take the core business and science (analytics) courses, but within each pathway, students have required electives to assist in their professionally guided curriculum. Your advisor will work with you to come up with your professionally guided curriculum based on your experience, professional background, and career goals.

For students with a background in Engineering, Analytics, Computer Science, Mathematics, Statistics, and related areas, the student is guided towards our traditional Technical Analytics track or AI & Analytics track. For students with a background in health/healthcare-related areas (undergrad degree in Biology, Pharmacy, Psychology, Pharmaceutical Sciences, and related areas), students are guided to our Health Informatics pathway.

For students with Finance related areas (undergrad degree in Finance, Business, Economics, Accounting, Business Intelligence, or related areas), students are guided to our Finance Analytics pathway.

For students with general business or management backgrounds, or with an interest in visualization, students are guided to our Business Intelligence & Analytics pathway.

Note that “in-person” sessions or courses listed can usually be attended via remote technology.

Business Core Courses - 5 courses (13 credits):

16:137:530 Principles of Finance and Accounting (3cr); 16:137:507 Market Assessment & Analysis (3cr); 16:137:502 Principles of Communication & Leadership (3cr); 16:137:500 Ethics (1cr);

16:137:600 Science & Technology Management Capstone (3cr): (Prerequisite Courses: 16:137:502,16:137:507, 16:137:530)

Analytics Core Courses - 5 courses (15 credits):

16:137:550 Fundamentals of Analytics (3cr); 16:137:538, OR 17:610:557 Database and Data Warehousing (3cr); 16:137:539 Intro to Cloud Computing & Big Data (3cr); 16:137:602 Regression Analysis (3cr); 16:137:551 Advanced Analytics & Practicum (3cr)

Health Informatics Pathway

Admissions Requirements: A Degree and/or work experience in healthcare, pharmaceutical sciences, psychology, and related areas. A year of calculus is required (Calc 1 and Calc 2). For those that did not take Calc 2, statistics can be substituted: Calc 1 and Stats 1 and 2 OR Calc 1 and BioStats 1 and 2 OR Calc 1 and Stats and Regression (separate) courses.

Business Electives
(2 courses = 6 credits)

Analytics Electives
(3 courses = 9 credits)

Business Analytics Programming OR Business Forecasting
16:137:552 Python Methodologies (3cr)
1 Elective
- Recommended: 16:137:653/654/655 Externship (unless the student still needs to take Basic Statistics)

Technical Analytics Pathway

Admissions Requirements: For those interested in analytics, typically with an engineering, stats, statistics, mathematics, operations research, or related degree. Must have taken Calc 1 & 2.

Business Electives
(2 courses = 6 credits)

Analytics Electives
(3 courses = 9 credits)

16:137:562 Applied AI from Concept to Market (3cr)
2 Electives
- Recommended: 16:137:653/654/655 Externship (unless the student still needs to take Basic Statistics)

Finance Analytics Pathway

Admissions Requirements: For those with a business, finance, economics, business intelligence, or accounting degree. A year of calculus is required (Calc 1 and Calc 2). For those that did not take Calc 2, statistics can be substituted. Calc 1 and Stats 1 and 2 OR Calc 1 and economic modeling and Econometrics.

Business Electives
(2 courses = 6 credits)

16:137:553 Bus. Intelligence Visual Analytics (3cr)*
Project Management*

Analytics Electives
(3 courses = 9 credits)

16:137:552 Python Methodologies (3cr)
2 Electives
- Recommended: 16:137:653/654/655 Externship (unless the student still needs to take Basic Statistics)
- 16:137:563 Basics of AI for Science Professionals (Cr. 3)
- 16:137:606 Special Topics: Data Storytelling (Cr. 3)

Business Intelligence & Analytics

Admissions Requirements: For those with a business, finance, economics, business intelligence, human resources, accounting, or related degree. A year of calculus is required (Calc 1 and Calc 2). For those that have taken Calc 1 or Business Calc 1 but did not take Calc 2 and are interested in this pathway, we accept a combination of either: Calc 1 and Stats 1 and 2, OR Calc 1 and economic modeling and Econometrics, OR Calc 1 and two upper levels of business modeling/quantitative courses. We accept the GRE or GMAT for those interested in this pathway (and waive testing requirement a Rutgers undergrad or grad degree, a US masters, MBA, or PhD, OR 5+ years work experience AND a US bachelors degree).

Business Electives

16:137:553 Business Intelligence with Visual Analytics (3cr)*
17:610:535 Competitive Intelligence (3cr)
Additional elective options listed here.

Analytics Electives

AI & Analytics

Admissions Requirements: For those interested in analytics, and have an engineering, computer science, stats, math, operations research, or related degree. Must have taken Calc 1 & 2.

Business Electives

Analytics Electives

16:137:552 Python Methodologies (3cr)
2 Electives
- Recommended: 16:137:653/654/655 Externship OR 16:198:520 Introduction to Artificial Intelligence (3cr) (unless the student still needs to take Basic Statistics)
- 16:137:563 Basics of AI for Science Professionals (Cr. 3)
- 16:137:606 Special Topics: Data Storytelling (Cr. 3)

Data Science & Security Intelligence

Admissions Requirements: For those interested in analytics, typically with an IT, computer science, management of information systems, engineering, statistics, mathematics, operations research, or related degree. Must have taken Calc 1 & 2, or calc 1 & two upper level statistics course, calc 1 & two upper level programming courses. Courses or professional experience in criminology, criminal justice, security, cybersecurity, security intelligence, or related are recommended.

Business Electives
(2 courses = 6 credits)

16:790:583 Public Health Infrastructure and National Security (3cr)
22:390:670 (or equivalent) Risk Management (3cr)
16:790:575 Global Politics of Internet Security (3cr)
16:790:558 Politics of Cyber Warfare (3cr)
Additional elective options listed here.

Analytics Electives
(3 courses = 9 credits)

16:137:561 Essentials of Cybersecurity and Secure Systems (3cr);
16:137:563 Basics of AI for Science Professionals (Cr. 3)
16:137:606 Special Topics: Data Storytelling (Cr. 3)
26:198:645 Data Privacy (3cr)
17:610:582 Information Policy (3cr)
26:198:643 Information Security (3cr)
17:610:567 Information Security Management (3cr)
16:790:### Cyber Security and Artificial Intelligence (3cr) (Special Topics in Polical Science if and when taught)
16:540:594 Risk Analysis and Mitigation (3)
16:540:505 Engineering Decision Making under Uncertainty (3)

Analytics & Supply Chain

Admissions Requirements: For those interested in analytics, typically with an engineering, supply chain, business, statistics, mathematics, operations research, or related degree. Must have taken Calc 1 & 2, or calc 1 & two upper level economics modeling courses, or calc 1 & two upper level statistics courses, or calc 1 & two upper level financial forecasting courses.

Business Electives

16:137:606 — Special Topics: Sustainability: Supply Chain Management Green Purchasing (Cr. 3)
16:137:525 - Introduction to Product Design and Development
34:970:553 Transportation and Environment (3)
34:970:554 Transportation and Land Use (3)
34:970:559 Transportation Risk and Security (3)
Additional elective options listed here.

Analytics Electives

16:540:594 Risk Analysis and Mitigation (3)
34:970:591 Introduction to Geographic Information Systems for Planning and Policy (3)
16:540:594 Risk Analysis and Mitigation (3)
16:540:505 Engineering Decision Making under Uncertainty (3)
16:137:563 Basics of AI for Science Professionals (Cr. 3)
16:137:606 Special Topics: Data Storytelling (Cr. 3)

Analytics: Design Thinking & Analytics

Admissions Requirements: For those interested in analytics, and have a degree in business, marketing, advertising, engineering, computer science, stats, math, operations research, or related degree. Must have taken Calc 1 & 2, or calc 1 & two upper level economics modeling courses, or calc 1 & two upper level statistics courses, or calc 1 & two upper level financial forecasting courses.

Business Electives

Analytics Electives

*16:137:553 Business Intelligence with Visual Analytics (3cr) is REQUIRED for all Analytics students and counts as a business elective.

*22:799:691 Project Management (3cr) OR 16:137:601 Project Management for Sci/Tech (3cr) can be taken.

16:137:552 Python Methodologies (3cr) is required in the first semester for any students who have never taken a programming course for academic credit.

01:960:484 Basic Statistics or 01:960:401 Basic Statistics for Research is required in the first semester for any students who have never taken an undergrad or higher-level statistics, biostatistics, or business statistics for academic credit and/or not received at least a B or better academic score in their course.

Degree Requirements

In addition to 19 credits of business courses and 24 credits of science courses, all MBS concentrations require additional degree requirements. See here for the full list of degree requirements.

If you have questions about the program curriculum, please contact the concentration coordinator(s) or request an appointment with an advisor.