Analytics: Discovery Informatics & Data Sciences (Online)
The Master's of Business and Science (MBS) degree in Analytics prepares students for data-driven decision making. The curriculum integrates courses in analytics/data science with courses in business and management, through a professionally guided curriculum and an emphasis on experiential learning. The MBS Analytics curriculum brings together the fields of computer science, statistics, machine learning, data mining and big data. Students will obtain a variety of skills including the ability to analyze large datasets, the ability to develop modeling solutions to support decision making, and a thorough understanding of how data analysis drives business decision making.
This concentration is a fully Online version of the traditional Master of Business & Science (MBS) degree with a concentration in Analytics. Classes will be online courses. Students complete the program in about 18-21 months if full-time (2-4 years if part-time). See below for on-site residency requirements, detailed curriculum, and application instructions.
If you are interested in our in-person/hybrid analytics option, click here.
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.
Pathways guide students of varying backgrounds (from health/biotech fields to finance and business fields to computer science or engineering fields) on where to start in analytics and how to progress through the concentration curriculum. The foundations of analytics are statistics and programming. For those with no or minimal backgrounds in these areas, we recommend starting with a basic statistics course and a basic programming course before moving into the core curriculum. For those coming from computer science and engineering backgrounds, we can recommend more advanced or challenging electives to stretch your skills.
Pathways available in the Online Analytics program:
- Health Informatics – for those with health or life science backgrounds and interests
- Finance Analytics – for those with finance related interests or backgrounds
- Business Intelligence & Analytics – for those with general business backgrounds or interests in visualization as used in business
- AI & Analytics – for those interested in AI
- Technical Analytics – for those with engineering, computer science, analytics and mathematics backgrounds
To see the full pathway descriptions, check the in-person/hybrid analytics webpage. Below, we provide a short overview of core courses, common requirements and the differences between the pathways that focuses on those courses available to fully online students. Descriptions of individual courses can be found by following the embedded links.
Overview of Analytics Curriculum
Business Core Courses - 5 courses (13 credits):
Note that “in person” sessions or courses listed can usually be attended via remote technology.
Principles of Finance and Accounting (16:137:530) – online sections available in Fall, Spring, and Summer semesters
Market Assessment & Analysis (16:137:507) – online section available Fall, Spring, and Summer semesters
Principles of Communication & Professional Development (16:137:502) – online section available Summer semester
Ethics (16:137:500) – always online (most sessions asynchronous; 3 synchronous/in-person sessions); taught Fall, Spring and Summer sessions
Science & Technology Management Capstone (16:137:600) – online sections available Fall and Spring (sections are synchronous with in person sections; final presentation REQUIRES in person presentations – see notes on “On-Campus Residency” below)
Prerequisites to Analytics Core Courses
Most of the Analytics core courses (and Analytics electives) require basic statistics and programming. For those who did not take programming or statistics as undergrads, the following courses are recommended:
Basic Statistics (01:960:484) or Basic Statistics for Research (01:960:401) - NOTE these are not available as online courses. Fully online students will need to seek out a local-to-them course and provide a transcript.
Python Methodologies (16:137:552) – hybrid (5-7 in person sessions) or online (any in-person sessions can be attended remotely) depending on semester
Analytics Core Courses - 5 courses (15 credits):
Note that “in person” sessions or courses listed can usually be attended via remote technology.
Fundamentals of Analytics (16:137:550) – taught Fall and Spring; online section is synchronous with in-person section (remote login)
Database and Data Warehousing (16:137:538 OR 17:610:557) – 16:137:538 taught in Spring (online section available); 17:610:557 taught Fall and Spring (online sections available)
Intro to Cloud Computing & Big Data (16:137:539) – taught in Fall only (online students attend remotely – synchronous)
Regression Analysis (16:137:602) – Spring 2020 has a mostly online version – some in-person meetings
Advanced Analytics & Practicum (16:137:551) – taught Fall semester only (online students attend remotely – synchronous; final presentation REQUIRES in person presentation.
An Example of a Part-Time course load for Health Informatics, Finance Analytics or Business Intelligence and Analytics
Opportunities in analytics are plentiful in the tri-state area (New York, New Jersey, Pennsylvania). This program prepares students for careers in predictive modeling, business intelligence, analytics, data mining in data-driven industries such as marketing, finance, health care, biotechnology and others. See this 2018 blog about the different options in Analytics and the skills needed to succeed. Understand how the skills differ by industry, and see below for detailed skills by industries relating to some of our Analytics Pathways. Our students have excellent outcomes, with a 96% employment rate within 6 months of graduation, working for companies such as JP Morgan, Barclays Investment Bank, Bloomberg LP, the Janssen Pharmaceutical Companies of Johnson & Johnson, Saatchi & Saatchi Wellness, Deloitte, Accenture, and more.
Matching Skills to the Careers You Want: We frequently perform labor analysis of skills requested by employers by industry. The four industries we target in a broad labor analysis match to our Analytics Pathways. These account for about 40% of the analytics roles requested by employers in 2018 (see chart below). These skills are utilized to help match students to electives and core courses. See HERE for further discussion on how we help match the skills you want to our courses.
Admissions Requirements: A bachelor’s degree in an appropriate field (mathematics, statistics, biostatistics, data mining, economics, marketing, IT, MIS, health sciences, finance/business, data/computer sciences, or engineering). A year of calculus is required (Calc 1 and Calc 2). For those that did not take Calc 2, two semesters of statistics or upper level financial or economic modeling can be substituted (please email the concentration coordinator or make an appointment with an Advisor to discuss if you are unsure).
For the Master of Business & Science (MBS) degree, students take 24 credits in the sciences and 19 credits in business. In addition, students must attend 12 colloquium events to qualify for graduation. Colloquium events can be outside professional meetings, professional development workshops or conferences related to the Concentration as well as MBS sponsored events.
The On-Site Residency in mandatory for all online students, including out-of-state students. For students in our fully online program, we have an on-campus "residency" for the capstone presentation and the analytics practicum presentation. During this time, you will be coming to campus for a 2-day visit during the capstone presentation. We cover the costs of the hotel stay (not travel). Click here for more information.
Other Information of Interest:
Externship Exchange: Students in this program are able to participate in company, nonprofit, research, and/or government real world projects to gain experience. These projects are done on campus in any semester (can be done every semester – fall, spring, summer), and are run by our Externship Exchange Coordinator, Dr. Christie Nelson (firstname.lastname@example.org). Projects can be done for volunteer/student club, or as an elective course to count toward the degree. These projects can be done remotely and in evenings for students working full time, online/hybrid students can participate, and full time/part time students can participate in daytime or evening to accommodate their schedules. These projects are yet another way to gain experience and help students to get to their professional goals.
Data Science Workshops: Students in this program are encouraged to attend the workshops in R, SAS, Stata, Python, Hadoop, etc. that run every semester. We also encourage you to attend the Practicum Poster Session. These are open to all students in the program. Please see the event list for scheduling.
Professional Services, Opportunities & Outcomes
To read more about our professional services (resume review, career services, and workshops), our Externship Exchange program (company/nonprofit projects that can be done in evenings in addition to working full time, remotely, or for full/part time students as elective credit or for “club”/volunteer), and more, see our Corporate Connections page. Our students have excellent outcomes, with a 96% employment rate within 6 months of graduation, working for companies such as JP Morgan, Barclays Investment Bank, Bloomberg LP, the Janssen Pharmaceutical Companies of Johnson & Johnson, Saatchi & Saatchi Wellness, Deloitte, Accenture, and more. We have a full time career services specialist for the MBS department, an executive coach, and real world on campus project opportunities to help get you to your professional goals.
This concentration is being coordinated in conjunction with the Rutgers Discovery Institute. While most of the course are in New Brunswick, NJ, some of the courses are also available at the Rutgers Newark and Camden campuses. For the In-Person Learning option, please see here.
Questions please contact: Dr. Christie Nelson email@example.com
Dr. Manish Parashar
Dr. Shantenu Jha
Dr. Deborah Silver
Dr. Debashis Kushary
Dr. William Pottenger
Dr. Karen Bemis
Dr. Christie Nelson