Catalog Entries |
Fall 2021
Apr 18,2024 |
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 | Select the Course Number to get further detail on the course. Select the desired Schedule Type to find available classes for the course. |
| DATA 101 - INTRODUCTION TO DATA SCIENCE |
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This course provides an introduction to data science and analytics through hands on analysis of real-world data Students will learn strategies for acquiring, processing, and utilizing data to make informed, data-driven decisions using computer based tools. Students learn and use the R programming language to understand these core data science skills.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Undergraduate Schedule Types: Hybrid, Lecture, Lecture/Online, Online Course Data Science Department |
| DATA 199 - TRANSFER ELECTIVE |
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This course designation is used to describe a transfer course from another institution which has been evaluated by the convener. A course with this course number has no equivalent Ramapo course. It may fulfill a requirement or may count as a free elective.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Undergraduate Schedule Types: Hybrid, Lecture, Online Course Data Science Department |
| DATA 225 - ETHICS OF TECHNOLOGY |
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This course presents a study of the impact of the computer on modem society. Positive and negative aspects of the use of the computer in such areas as the military, education, medicine, the office, the assembly line, databases, and the computerization of the home will be examined. This course will also take a deeper look into the collection, manipulation, and use of data. The course will include, but not be limited to, privacy concerns, security techniques, data anonymization, and proper vs. misuse of collected data.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Undergraduate Schedule Types: Hybrid, Lecture, Lecture/Online, Online Course Data Science Department Course Attributes: Gen Ed 18-Values and Ethics, WRITING INTENSIVE |
| DATA 299 - TRANSFER ELECTIVE |
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This course designation is used to describe a transfer course from another institution which has been evaluated by the convener. A course with this course number has no equivalent Ramapo course. It may fulfill a requirement or may count as a free elective.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Undergraduate Schedule Types: Hybrid, Lecture, Online Course Data Science Department |
| DATA 301 - DATA ANALYSIS & VISUALIZATION |
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This course introduces students to data visualization techniques commonly used in Data Science and Analytics. Students will learn the principles of presenting data to effectively communicate data-driven findings, using 2D and 3D charts, graphs, and more complex visualization methods. Students will learn to use Python, including NumPy, SciPy, Pandas, Matplotlih, and Plotly to apply these principles to existing
data sets.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Undergraduate Schedule Types: Hybrid, Lecture, Lecture/Online, Online Course Data Science Department |
| DATA 399 - TRANSFER ELECTIVE |
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This course designation is used to describe a transfer course from another institution which has been evaluated by the convener. A course with this course number has no equivalent Ramapo course. It may fulfill a requirement or may count as a free elective.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Undergraduate Schedule Types: Hybrid, Lecture, Online Course Data Science Department |
| DATA 450 - DATA SCIENCE CAPSTONE PROJECT |
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This course provides an opportunity for students to Work on an extensive project to produce a solution to a data related problem. Students will present the results of their Work as part of this course. This course serves as a capstone to the Data Science major and is Writing Intensive.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Undergraduate Schedule Types: Hybrid, Lecture, Lecture/Online, Online Course Data Science Department Course Attributes: WRITING INTENSIVE |
| DATA 499 - TRANSFER ELECTIVE |
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This course designation is used to describe a transfer course from another institution which has been evaluated by the convener. A course with this course number has no equivalent Ramapo course. It may fulfill a requirement or may count as a free elective.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Undergraduate Schedule Types: Hybrid, Lecture, Online Course Data Science Department |
| DATA 500 - IS: |
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Limited opportunities to enroll for course work on an Independent Study basis are available. A student interested in this option should obtain an Independent Study Registration Form from the Registrar, have it completed by the instructor and school dean involved, and return it to the Registrar's Office. Consult the current Schedule of Classes for policies concerning Independent Study.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Graduate Schedule Types: Independent Study Data Science Department |
| DATA 501 - PROGRAMMING FUNDAMENTALS FOR DATA SCIENCE |
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This course teaches the essential programming skills necessary to enroll in MSDS courses. The course focuses on Python, and provides a basic understanding of how computer programs are developed, designed, and tested. This course is offered as P/F.
0.000 TO 1.500 Credit hours 0.000 TO 1.500 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Hybrid, Lecture, Online Course Data Science Department Course Attributes: DATA COURSE FOR GRAD FEE ASSES |
| DATA 502 - PROBABILITY AND STATISTICS FOR DATA SCIENCE |
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The course covers topics typical in a first semester probability and statistics course with a view towards Data Science. This course is part of the bridge program for students entering the Master’s in Data Science with insufficient coursework or a refresher needed to be prepared for graduate work in Data Science. This course is offered as P/F.
0.000 TO 1.500 Credit hours 0.000 TO 1.500 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Hybrid, Lecture, Lecture/Online, Online Course Data Science Department Course Attributes: DATA COURSE FOR GRAD FEE ASSES |
| DATA 503 - LINEAR ALGEBRA FOR DATA SCIENCE |
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This course covers the key concepts from Linear Algebra that have applications in Data Science. These are typical topics taught in an Applied Linear Algebra course. This course is part of the bridge program for students entering the Master’s in Data Science with insufficient coursework or a refresher needed to be prepared for graduate work in Data Science. This course is offered as Pass/Fail.
0.000 TO 1.500 Credit hours 0.000 TO 1.500 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Hybrid, Lecture, Lecture/Online, Online Course Data Science Department Course Attributes: DATA COURSE FOR GRAD FEE ASSES |
| DATA 590 - TOPICS: |
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The descriptions and topics of this course change from semester-to-semester, as well as from instructor-to-instructor. Prerequisite: varies with the topic offered.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Hybrid, Lecture, Lecture/Online, Online Course Data Science Department Course Attributes: DATA COURSE FOR GRAD FEE ASSES |
| DATA 599 - TRANSFER ELECTIVE |
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This course designation is used to describe a transfer course from another institution which has been evaluated by the convener. A course with this course number has no equivalent Ramapo course. It may fulfill a requirement or may count as a free elective.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Graduate Schedule Types: Hybrid, Lecture, Online Course Data Science Department |
| DATA 600 - I.S.: |
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Limited opportunities to enroll for course work on an Independent Study basis are available. A student interested in this option should obtain an Independent Study Registration Form from the Registrar, have it completed by the instructor and school dean involved, and return it to the Registrar's Office. Consult the current Schedule of Classes for policies concerning Independent Study.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Graduate Schedule Types: Independent Study Data Science Department |
| DATA 601 - INTRODUCTION TO DATA SCIENCE |
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This course serves as the foundation for all DATA graduate level coursework. It will cover programming, data analysis, data visualization, ethics and security/privacy concerns surrounding data and other topics students are expected to master in the program. The course will also feature a Seminar component designed to acclimate students to working with industry Sponsors and to hear first hand from people working in Data Science.
0.000 TO 3.000 Credit hours 0.000 TO 3.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Hybrid, Lecture, Lecture/Online, Online Course Data Science Department Course Attributes: DATA COURSE FOR GRAD FEE ASSES |
| DATA 620 - ETHICS FOR DATA SCIENCE |
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This course is focused on ethical concerns, case studies, and discussion revolving around the acquisition, storage, and usage of data in Data Science. The course will include, but not be limited to, privacy concerns, security techniques, data anonymization, and proper vs. misuse of collected data.
0.000 TO 3.000 Credit hours 0.000 TO 3.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Hybrid, Lecture, Lecture/Online, Online Course Data Science Department Course Attributes: DATA COURSE FOR GRAD FEE ASSES |
| DATA 670 - DATA VISUALIZATION |
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The course provides students with the fundamental concepts and tools needed to understand the emerging role of data visualization in organizations. Students will learn techniques and algorithms for creating effective visualizations based on principles from graphic design, visual art, perceptual psychology, and cognitive science. The course will also provide a tool based exposure for visualization and communication of the visual analysis. This course is cross listed with MBAD670.
0.000 TO 3.000 Credit hours 0.000 TO 3.000 Lecture hours Levels: Graduate Schedule Types: Hybrid, Lecture, Online Course Data Science Department Course Attributes: DATA COURSE FOR GRAD FEE ASSES |
| DATA 690 - TOPICS |
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The descriptions and topics of this course change from semester-to-semester, as well as from instructor-to-instructor. Prerequisite: varies with the topic offered.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Hybrid, Lecture, Lecture/Online, Online Course Data Science Department Course Attributes: DATA COURSE FOR GRAD FEE ASSES |
| DATA 699 - TRANSFER ELECTIVE |
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This course designation is used to describe a transfer course from another institution which has been evaluated by the convener. A course with this course number has no equivalent Ramapo course. It may fulfill a requirement or may count as a free elective.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Graduate Schedule Types: Hybrid, Lecture, Online Course Data Science Department |
| DATA 730 - DATA SCIENCE FIELDWORK I |
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This is a projects-based course, developed in conjunction with industry sponsors and faculty. Students work closely with faculty and sponsors over one or more semesters on a domain-specific Data Science project. The program merges aspects of a co-op or internship and faculty-mentored independent study or thesis Students will be required to file progress reports with the faculty project mentor, along with a final presentation submitted to the project stakeholders and Data Science convening group. Opportunities to enroll in this course are subject to the availability of projects sponsored by the College.
industry or government representatives, or faculty. Availability will be announced prior to each semester, and students may enroll in the course to fulfill one of their Data Science electives. Enrollment will be granted at the discretion of participating faculty and the Data Science program director.
0.000 TO 3.000 Credit hours 0.000 TO 3.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Hybrid, Lecture, Online Course Data Science Department Course Attributes: DATA COURSE FOR GRAD FEE ASSES |
| DATA 731 - DATA SCIENCE FIELDWORK II |
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This course is a second, optional projects-based course, developed in conjunction with industry sponsors and faculty. Students participating in projects spanning two semesters will enroll first in DATA 730, and then this course to complete their multi-semester project. Students Work closely With faculty and sponsors over one or two semesters on a domain-specific Data
Science project. The program merges aspects of a co-op or internship and faculty-mentored independent study and thesis. Students will be required to submit periodic progress reports to the faculty project mentor, and give a final presentation to the project stakeholders and Data Science convening group near the end of the semester.
0.000 TO 3.000 Credit hours 0.000 TO 3.000 Lecture hours Levels: Graduate Schedule Types: Hybrid, Lecture, Online Course Data Science Department Course Attributes: DATA COURSE FOR GRAD FEE ASSES |
| DATA 750 - DATA SCIENCE THESIS |
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All M.S. students will be required to complete a Master’s Thesis under the advisement of a faculty member. This requirement is distinct from any Fieldwork Experiences the students participate in - however, students participating in Fieldwork Experiences for more than one semester may have their thesis requirement waived. Thesis projects represent independent research, developed and implemented by the student. Thesis projects require a written thesis to be submitted to the faculty advisor, along with a panel of Data Science faculty. The project also requires an oral presentation, made to the faculty advisor and panel. Grading is P/F for this course. Enrollment requires students meet with the Data Science Graduate Program Director, obtain approval of a project idea, and select a faculty advisor prior to registration. Registration for Spring semester requires project approval and advisor selection prior to the end of October, registration for Fall semester requires project approval and advisor selection prior to the end of April.
0.000 TO 3.000 Credit hours 0.000 TO 3.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Hybrid, Lecture, Lecture/Online, Online Course Data Science Department Course Attributes: DATA COURSE FOR GRAD FEE ASSES |
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