Description

 The basics of linear algebra and differential equations, with an emphasis on general physical and
engineering applications. Aimed at students who need the material for future coursework but do not
need as much depth and rigor as provided by MATH240/MATH461 and MATH246.

Prerequisites

 a C- or better in MATH 141

Topics

  1.  First-Order Differential Equations
    Differential equations and mathematical models
    General and particular solutions
    Linear equations and integrating factors
    Separable equations
    Exact equations
  2. Mathematical Models and Numerical Methods
    Population models
    Equilibirum solutions and stability
    Phase portraits
    Euler's method and improved Euler's method
  3. Linear Systems and Matrices
    Matrices and linear systems; row reduction and Gaussian elimination
    Reduced row echelon form; matrix operations
    Matrix inverses and determinants
    Linear equations and curve-fitting
  4. Vector Spaces
    R^n as a vector space and subspaces
    Linear combinations and independence of vectors
    Bases and dimension; column space and row space of a matrix
    Orthogonal vectors
  5. Higher-order Differential Equations
    Second-order linear equations; principle of superposition
    Homogeneous constant-coefficient equations
    Non-homogeneous equations; the method of undetermined coefficients
    Mechanical vibrations; forced oscillations and resonance
  6. Eigenvalues and Eigenvectors
    Eigenvalues and eigenvectors of matrices
    Diagonalization of matrices
  7. Linear systems of Differential Equations
    First-Order systems and applications
    The Eigenvalue method for linear systems
    Classification of phase portraits of linear planar systems
  8. Matrix Exponentials
    Matrix exponentials and linear systems
    Nonhomogeneous linear systems
  9. Nonlinear systems
    Stability and the phase plane for nonlinear systems; linear and almost-linear systems
  10. Laplace Transform Methods
    Laplace transforms and their inverses
    Applications to piecewise continuous forcing functions

Description

Introduction to effective and intuitive visual representations of data, including customizing graphics, plotting arrays, statistical graphics, and representing time series.

Prerequisites

STAT100, MATH135, or any 400 level STAT course; and DATA110 or DATA120.

Topics

Description

An introduction to data science i.e., the end-to-end process of going from unstructured, messy data to knowledge and actionable insights. Provides a broad overview of several topics including statistical data analysis, basic data mining and machine learning algorithms, large-scale data management, cloud computing, and information visualization.

Prerequisites

DATA110 or DATA120; and DATA200 and DATA250; or by permission of the DATA Program Director.
Restriction: Must not be a Computer Science major.
Jointly offered with: CMSC320.
Credit only granted for: CMSC320 or DATA320

Topics

Description

 Introduction to basic discrete mathematical and linear algebraic structures and use of these mathematical structures to solve programming problems. Logic, set theory, formal proof methodology, functions, and basic linear algebra.

Prerequisites

DATA110 or DATA120; and MATH141.

Topics

Description

 Course dedicated to the study of ethical issues associated with data science, including data collections, gathering existing data, ethical use of data, data analysis with teams, repeatability and reproducibility of data analysis, and academic and scientific integrity.

Prerequisites

STAT100, MATH135, or any 400-level STAT course.

Topics