Website: School of Theoretical and Applied Science
Convener:
Faculty:
- Matthew Jobrack
- Osei Tweneboah
- Debbie Yuster
- Current as of June 2020
Data Science is new emerging field with a high demand in the employment market. There are many unfilled positions on job boards, particularly in the New Jersey and New York areas. The Bureau of Labor and Statistics it as among the fastest growing in the next 10 years with over a 25% rate. Thus, these jobs are going unfilled currently and there will be need for more in the future. So, a degree in Data Science prepares you for these positions.
Ramapo College offers a three-featured program with a core set of classes, a disciplinary minor (or double major), and a capstone research project. The core classes are designed for students to learn the technical skills necessary for data analysis, including statistics, computer programming, ethics, data visualization, communications, and data analysis. The project-based curriculum exemplifies how and why the disciplinary knowledge is so critical in converting data into information. Each student selects a required minor or double major to learn much deeper and more broadly the background information necessary to be an effective data scientist. The culminating experience of this program is a capstone project in which the students produces a solution to a data related problem from their minor (or double major) field of study. This structure best prepares students for either graduate school or employment.
Learning Goals/Outcomes for the program
Goal 1: Develop problem solvers
Outcome 1: Students will demonstrate the ability to solve data-related problems.
Goal 2: Develop effective communicators
Outcome 2: Students will communicate data findings effectively to any audience, orally, visually and in written formats.
Goal 3: Develop ethical and technically proficient professionals
Outcome 3: Students will demonstrate an understanding of ethical aspects of data management and reporting.
Outcome 4: Students will perform basic technical skills to prepare data for analysis.
Outcome 5: Students will appropriately formulate and use data analyses through computing, programming, statistical, and mathematical tools.
Goal 4: Develop effective interdisciplinary team members
Outcome 6: Students will apply data analytic techniques to applications in another discipline
- Transfer students who have 48 or more credits accepted at the time of transfer are waived from the courses marked with a (W) below. Waivers do not apply to Major Requirements.
- Double counting between General Education and Major may be possible. Check with your advisor to see if any apply.
- Writing Intensive Requirement (five courses): two writing intensive courses in the general education curriculum are required: Critical Reading and Writing and Studies in the Arts and Humanities the other three courses are taken in the major.
- Not all courses are offered each semester. Please check the current Schedule of classes for semester course offerings.
- All students are required to declare and complete a minor or a second major to successfully graduate from the program.
DATA SCIENCE MAJOR
- Subject & Course # – Title & Course Description
- GENERAL EDUCATION REQUIREMENTS
- REQUIRED – CRWT 102 - CRITICAL READING AND WRITING II
- SELECT ONE – INTD 101 - FIRST YEAR SEMINAR OR
- HNRS 101 - HONORS FIRST YEAR SEMINAR *
- SELECT ONE – AIID 201 - STUDIES IN ARTS & HUMANITIES OR (W)
- HNRS 201 - HONORS STUDIES IN THE ARTS AND HUMANITIES *
- SELECT ONE – SOSC 110 - SOCIAL SCIENCE INQUIRY OR (W) (Formerly SOSC 101)
- HNRS 110 - HONORS SOCIAL SCIENCE INQUIRY *
- SELECT ONE – (W) - HISTORICAL PERSPECTIVES CATEGORY
- SELECT ONE – (W) - GLOBAL AWARENESS CATEGORY *
- SELECT ONE – - QUANTITATIVE REASONING CATEGORY Suggested MATH 121 - CALCULUS I
- SELECT ONE – - SCIENTIFIC REASONING CATEGORY
- SELECT TWO – DISTRIBUTION CATEGORY (One course must be outside of school)
- * Students in the College Honors Program must take the HNRS course options.
- DATA SCIENCE MAJOR REQUIREMENTS
- MATHEMATICS REQUIRED (12 CREDITS)
- MATH 237 - DISCRETE STRUCTURES OR (WI)
- MATH 205 - MATHEMATICAL STRUCTURES (WI)
- MATH 262 - LINEAR ALGEBRA(WI)
- MATH 370 - APPLIED STATISTICS
- COMPUTER SCIENCE REQUIREMENTS (16 CREDITS)
- CMPS 130 - SCI PROBLEM SOLVING-PYTHON
- CMPS 240 - DATA ANALYTICS IN PYTHON
- CMPS 320 - MACHINE LEARNING
- CMPS 364 - DATABASE DESIGN
- DATA SCIENCE REQUIREMENTS (16 CREDITS)
- DATA 101 - INTRODUCTION TO DATA SCIENCE
- DATA 225 - ETHICS OF TECHNOLOGY (WI)
- DATA 301 - DATA ANALYSIS & VISUALIZATION
- DATA 450 - DATA SCIENCE CAPSTONE PROJECT (WI)
- ELECTIVES (4 CREDITS)
- CMPS 310 - BIG DATA PROGRAMMING
- CMPS 369 - WEB APPLICATION DEVELOPMENT
- MATH 390 - ADVANCED TOPICS (in Math Modeling)
- CAREER PATHWAYS REQUIREMENTS
- Visit the Cahill Career Center / Cahill Office
- SCIN 001 - CAREER PATHWAYS MODULE 1
- SCIN 002 - CAREER PATHWAYS MODULE 2
- SCIN 003 - CAREER PATHWAYS MODULE 3
- REQUIRED MINOR OR SECOND MAJOR
- Completion of a Minor or Second Major Required for Graduation
- Consult with an Academic Advisor before declaring the required minor or second major
- Visit the Office of the Registrar to declare a minor or additional major.
For more information, please contact Professor Amanda Beecher, Convener, Data Science, Room G-128H, (201) 684-7159 or abeecher@ramapo.edu