Computer Science Course Description
CSC 101 – Introduction to Computer Science (3 credits)
This course provides an introduction to a disciplined approach to computer programming and problem solving, utilizing a block-structured high-level language, with an emphasis on procedural abstraction and good programming style. Students will apply programming skills in solving a variety of problems. Algorithmic concepts are also introduced. This course also provides a survey study of data structures and data abstraction, and an introduction to complexity considerations and program verification.
Prerequisite: None. Co-requisite: MAT 101 or MAT 105.
CSC 112 – Programming I (4 credits)
This course offers an overview of computer hardware and software, programming in C with emphasis on modular and structured programming technique, problem solving and algorithm development, simple engineering and scientific problems, basic data types and operators, basic object-oriented concepts, wrapper classes, console input/output, logical expressions and control structures, classes, arrays, and strings.
Mathematics and Statistics Course Description
MAT 100 – Pre-calculus for CoB (3 credits)
This course builds sound and strong basic mathematics that are required for studying undergraduate mathematics. This course is particularly important to students whose mathematical skills are not sufficiently developed at the high school level. The course covers materials that include algebraic operations, radical and rational expression, equalities and in-equalities, functions and analytic geometry, special types of functions (linear, quadratic, inverse, polynomial, rational, exponential, logarithmic and trigonometric), solution to equations, and identities involving some types of functions.
MAT 101 - Calculus I (4 credits)
This course introduces the basic concepts of mathematical analysis used in science and engineering. The course teaches an introduction to differential and integral calculus. Topics include limits; the derivative; rates; Newton's method; the mean-value theorem; max-min problems; the integral and the fundamental theorem of integral calculus; areas, volumes, and average values.
MAT 102 – Pre-calculus for CoM (2 credits)
This course will cover basic topics in algebra and serves as an introduction to trigonometry. Topics covered include the real line and coordinate system, functions and graphs, symmetry and translation, inverse functions, polynomial and rational functions, exponential and logarithmic functions, trigonometric functions and special identities. Some applications of these concepts to problems that may be helpful to the further study of quantitative methods in the medical sciences will be considered.
MAT 105 – Calculus for Biomedical Sciences I (4 credits)
This course offers a solid introduction to differential and integral calculus and is designed for students in the biomedical sciences. The course begins with an intensive review of important topics from pre-calculus and an introduction to discrete time and population models. Then it proceeds to cover limits, continuity, differentiation, derivative rules, curve sketching, optimization, difference equations, anti-derivatives, Riemann sums, definite integral, fundamental theorem of calculus, applications of integration.
UPP College Algebra or Equivalent.
MAT 111 - Business Calculus (3 credits)
The main objective of this course is to help the student in understanding the basic concepts of calculus on the one hand, and to develop the skills needed for using calculus as a viable tool to solve problems that arise in the study of business and economics. Topic covered include, limits, types of functions (polynomial, rational, exponential and logarithmic), their derivatives, anti-derivatives and their various applications.
MAT 112 - Calculus II (4 credits)
This course is a continuation to Calculus I. The course covers basic mathematical analysis and mathematical tools that are widely used and are essential for mathematical analysis and applications. Topics include sequences; infinite series; power series; conics; polar, cylindrical, and spherical coordinates; vectors and the geometry of space; and vector valued functions.
MAT 116 – Calculus for Biomedical Science II (4 credits)
This course is a continuation of MAT 105. The course covers further integration techniques, such as integration by parts, by substitution and by partial fractions. Other topics include improper integrals, sequences and series, convergence tests, power and Taylor series, solving differential equations, limits and continuity of functions of two variables, partial derivatives, the double integral.
MAT 211 - Calculus III (3 credits)
This course deals with multi-dimensional calculus. It is designed primarily for engineering majors and is taken by other technical majors. The student will develop an understanding of limits and continuity of functions of several variables; compute partial derivatives and apply to optimization problems; set up and compute iterated integrals to compute areas, volumes of solids; understand and apply Green's Theorem, the Divergence Theorem and Stoke's Theorem.
MAT 212 - Linear Algebra (3 credits)
The course teaches an introduction to linear algebra. Topics include complex numbers, geometric vectors in two and three dimensions and their linear transformations, the algebra of matrices, determinants, solutions of systems of equations, vector space, eigenvalues and eigenvectors.
MAT 213 Differential Equations (3 credits)
This course is an introduction to the theory and application of ordinary differential equations and the Laplace transform. The main objective is for the student to develop competency in the basic concepts and master certain solution methods. Topics covered include linear and nonlinear first order equations; higher order linear differential equations; undetermined coefficients method; variation of parameters method; Cauchy-Euler equation; Laplace transform; linear systems solution; solution by series method.
MAT 224 Numerical Methods (3 credits)
This course introduces the basic concepts of numerical analysis that are employed in science and engineering. It includes a solid introduction to the basic methods and approximation techniques in use, and to the reliability and accuracy of the approximations. Applications of the methods to simplified/model problems that represent real-life problems are also included. Programming skills (based on MATLAB) needed to implement the methods on a computer are also covered.
STA 211 - Probability and Statistics (3 credits)
STA 211 introduces the basics of probability and statistics as used in sciences. It covers introduction to probability, random variables, some common probability distributions, random vectors, sample statistics, regression, and applications in life sciences.
STA 212 - Probability and Statistics for Engineers (3 credits)
The course is designed to teach students the basics of probability and statistics as used in engineering and the sciences. The course covers introduction to probability theory, random variables, statistics, and regression.
MAT 320 – Partial Differential Equations for Scientists and Engineers (3 credits)
This course deals with partial differential equations: first order equations (linear and nonlinear), heat equation, wave equation, and Laplace equation. Separation of variables. Method of characteristics for hyperbolic problems. Solution of initial boundary value problems using separation of variables and Eigen function expansions. Some numerical methods.
MAT 212, MAT 213.
MAT 321 – Advanced Calculus (3 credits)
Detailed and analytical study of differential and integral calculus for types of functions of several variables; implicit function theorem, vector calculus; line, surface, and space integrals including Green's theorem, Divergence theorem, and Stokes' theorem.
MAT 211, MAT 212.
MAT 322 – Complex Variables for Scientist and Engineers (3 credits)
This course is an introduction to complex variables accessible to juniors and seniors in engineering, physics and mathematics. The algebra of complex numbers, analytic functions, Cauchy Integral Formula, theory of residues and application to the evaluation of real integrals, conformal mapping and applications to physical problems.
MAT 420 – Advanced Probability and Stochastic Process (3 credits)
The objective of this course is to introduce the fundamental principle of probability measure theory and to introduce to stochastic processes. Large sample with a variety of convergence concepts and central limit theorems are included as first part. The second part is dedicated to stochastic processes that help students to model the complete evolution of the system related to telecommunication, Finance, Biology, and Physics. Topics will include branching processes, Random walk, Brownian motion, Markov processes, counting processes and discrete processes with the Markov property.
MAT 112, STA 212.