Fall 2022 DMC Course Schedule

1st Year Students

Welcome to Ramapo College of New Jersey! Whether you are entering the MS in Data Science, Applied Mathematics, or Computer Science, there are a few things you will want to take care of to get ready for your first semester. Admissions has a guide for admitted students, which outlines the registration process and a number of other things of interest.

Fall 2022 Course Schedule

• CMPS 547 – Foundations of Computer Science

  This course provides a foundational overview of programming language design, including compiled languages as well as higher level scripting languages. The course introduces students to concepts such as grammars, binding, scope, flow control, and data abstraction – through the lense of multiple languages. Students will also gain experience programming across language interfaces. This course serves 3 core purposes as a foundational course for MSCS students: (1) Principles of Programming Languages – this course serves as a general introduction to the theory of computation and programming language design. Topics cover basic theory of computation, and language principles such as context free grammars; binding and scope; static and dynamic semantics; type safety; recursion; concurrency. The theoretical topics covered throughout the course will be demonstrated / mapped to the programming topics languages introduced. (2) The C programming language – students are introduced to the C as a way to prepare them for courses such as Operating Systems and so they understand aspects of low level programming language to support the Computer Architecture course as well. The fundamental topics in C include types, control flow, structures, arrays, pointers, and relationship to hardware via compilation. (3) Python Programming – students will learn how higher level languages differ from C, and how they map to lower level languages. Significant time will be spent covering a variety of language concepts through the lens of Python, culminating with extending Python via C through Cython.

  Monday nights – 6:05pm – 7:20pm

  Required for MS Computer Science first year students.
  Category 2 elective for MS Applied Mathematics students

• MATH 680 – Advanced Mathematical Modeling

  This course requires students to develop, use, and assess models to solve real-world problems using the mathematical modeling process. Models developed in a variety of disciplines, including linear programming, network science, decision theory, machine learning, are studied and used to solve problems in other disciplines.

  Monday nights – 6:05pm – 7:20pm

  Required for MS Data Science second year students.
  Required course for MS Applied Mathematics students (any year, with pre-requisites).
  Category 2 elective for MS Computer Science students (with pre-requisites).

• DATA 601 – Introduction to Data Science

  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.

  Tuesday nights – 6:05pm – 7:20pm

  Required for MS Data Science first year students.
  Category 2 elective for MS Applied Mathematics (recommended for first year students).

• MATH 570 – Applied Statistics

  This course gives an introduction to statistical methods used in data science with an emphasis on applications. Topics may include foundations of probability, univariate and multivariate random variables and distributions, special distributions, Central Limit Theorem, one- and two-sample methods, point estimation, interval estimation, hypothesis testing, regression analysis, Bayesian analysis, data analysis and model building.

  Tuesday nights – 8pm – 9:15pm

Required for MS Data Science full time first year students. May be deferred to future semester for part time MSDS students.
Required for MS Applied Mathematics students full time first year students. May be deferred to future semester for part time MSAM students.
Category 2 elective for MS Computer Science students (recommended for first year students).

• CMPS 530 – Python for Data Science

  This course introduces students to fundamental programming concepts and skills utilized by Data Scientists – in particular parallel computing, I/O, and visualization – all through the Python programming language and associated libraries (i.e. numpy, pandas, etc.). The course is suitable for students with a basic knowledge of programming, and prepares students to take more advanced computing courses in databases, big data analytics, machine learning, and other DATA and CMPS electives.

  Thursday nights – 6:05pm – 7:20pm

  Required for MS Data Science full time first year students. May be deferred to future semester for part time MSDS students.
  Category 2 elective for MS Applied Mathematics students (strongly recommended for first year students).
  Category 1 elective for MS Computer Science students (recommended for first year students).

• MATH 562 – Applied Linear Algebra

  This course is a foundational course for the study of Linear Algebraic structures used in a variety of scientific and computational applications, such as data fitting, clustering, feature engineering, image processing, machine learning, optimization, and dynamical systems. In order to achieve this purpose, this course will cover topics in linear algebra including vector and matrix operations, linear transformations, linear independence, norms, decomposition, and least squares.

  Thursday nights – 8pm – 9:15pm

Category 1 elective for MS Data Science students.
Required for MS Applied Mathematics (strongly recommended for first year students).
Category 2 elective for MS Computer Science students (recommended for first year students).

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