Required Area Courses

MATH 106 – Calculus I
Credits: 3
Limits and continuity; derivative and properties of differentiable functions; mean value theorems, Taylor’s formula, extreme values; indefinite integral and integral rules; Riemann integral and fundamental theorem of calculus; L’Hospital’s rule; improper integrals.

PHYS 101 – General Physics I
Credits: 3
Corequisites: Must be taken with PHYS 101L or consent of the instructor
Physical quantities; rectilinear motion; motion in two and three dimensions; Newton’s laws of motion; work and energy; momentum; conservation laws; collisions; rotational dynamics; gravitation; periodic motion; fluid motion.

PHYS 101L – General Phys I Lab
Credits: 1
Prerequisites: Must be taken with PHYS 101 or consent of the instructor
General physics laboratory course to accompany PHYS 101. Experiments in mechanics.

INDR 100 – Introduction to Industrial Engineering
Credits: 3
Prerequisites: Must be taken with PHYS 101 or consent of the instructor
Introduction to industrial engineering concepts. Fundamentals of systems analysis and modeling. Basics of production and service systems. Computer and programming applications of several industrial engineering topics. Hands-on experience for industrial engineering subjects in team projects.

MATH 107 – Introduction to Linear Algebra
Credits: 3
Vectors; Vectors; matrices and systems of linear equations; vector spaces; linear maps; orthogonality; algebra of complex numbers; eigenvalue problems.

MATH 203 – Multivariable Calculus
Credits: 3
Prerequisites: MATH 106 or consent of the instructor
Functions of several variables; partial differentiation; directional derivatives; exact differentials; multiple integrals and their applications; vector analysis; line and surface integrals; Green’s, Divergence and Stoke’s theorems.

PHYS 102 – General Physics II
Credits: 1
Prerequisites: PHYS 101 or consent of the instructor and must be taken with PHYS 102L
Electric charge and electric field; Gauss’s law; electric potential; dielectrics; electric circuits; magnetic field and magnetic forces; sources of magnetic field; electromagnetic induction; electromagnetic waves.

PHYS 102L – General Physics II Lab
Credits: 1
Prerequisites: Corequisite: Must be taken with PHYS 102
Electric charge and electric field; Gauss’s law; electric potential; dielectrics; electric circuits; magnetic field and magnetic forces; sources of magnetic field; electromagnetic induction; electromagnetic waves.

COMP 125 – Programming with Python
Credits: 3
This course emphasizes computational thinking and programming using Python. Gain a solid foundation in algorithmic thinking and structured programming, and perform basic, common computational tasks easily and efficiently. Examine the fundamentals of data storage, input and output, control structures, functions, sequences and lists, file I/O, graphics, and objects.

ENGR 200 – Probability and Random Variables for Engineers
Credits: 4
Prerequisites: MATH 106 or consent of the instructor
Introduction to probability, sets, conditional probability, total probability theorem, and Bayes rule; Independence, counting; Discrete random variables, functions of random variables, expectation, mean and variance; Continuous random variables, probability density functions, and cumulative distribution functions; Multiple random variables; Sums of random variables; Limit theorems; Covariance and correlation; Introduction to Stochastic Processes.

INDR 201 – Discrete Mathematical Structures
Credits: 3
Prerequisites: MATH 106 or consent of the instructor
Fundamentals of logic, mathematical induction, basic set theory, relations and functions, fundamental principles of counting, inclusion-exclusion principles, basic graph theory, trees, algorithms for basic industrial engineering, and operations research problems on graphs and networks.

MATH 204 – Differential Equations
Credits: 3
Prerequisites: MATH 107 or consent of the instructor
First order differential equations. Second order linear equations. Series solutions of ODE’s. The Laplace transform and applications. Systems of first order linear equations. Nonlinear equations and systems: existence, uniqueness, and stability of solutions. Fourier series and partial differential equations.

MBGE 200 – Introductory Biology
Credits: 3
Principles of biochemistry; molecular and cell biology. General introduction to cell structure and function. Genetics, bioenergetics, anatomy, and physiology; introduction to biotechnology.

INDR 202 – Engineering Economics
Credits: 3
Financial accounting principles and cost systems for engineering economic analyses. Cost-volume-profit analyses, discounted cash flow, and budgeting techniques.

INDR 220 – Introduction to Computing For Operations Research
Credits: 3

Prerequisites: COMP 125 and INDR 100 and MATH 107
A broad introduction to scientific computing, linear algebra and scientific computing libraries; formulating optimization problems for real-life scenarios and algebraic representations of optimization models; introduction to commercial optimization solvers; solving linear programming, (mixed) integer linear programming, unconstrained nonlinear programming, quadratic programming, and quadratically constrained quadratic programming models using optimization solvers; formulating statistical models as optimization problems and solving them using optimization solvers.

INDR 252 – Applied Statistics
Credits: 3
Prerequisites: ENGR 200 or consent of the instructor
Basic parametric statistics such as estimation, confidence intervals, and hypothesis testing. Distribution fitting, goodness of fit tests. Independence tests and contingency tables. Simple linear regression and correlation analysis. Nonlinear and multiple regression, analysis of categorical data. Industrial engineering applications in quality control and demand forecasting. Statistical software packages and computer implementations.

INDR 262 – Introduction to Optimization Methods
Credits: 4
Prerequisites: INDR 200 and (MATH. 107 or MATH 106) or Consent of the instructor
Introduction to modeling concepts and optimization; setting upoptimization models from problem description; linear programming problem formulation; simplex method, duality and sensitivity analysis; applications of mathematical programming in engineering and management with computer implementations.

INDR 291 – Summer Practice I
Credits: 0
Prerequisites: INDR 100 and (INDR 252 or INDR 262) and ACWR 101
A minimum of 20 working days of training in an industrial summer practice program after the completion of second year. The training is based on the contents of the “Summer Practice Guide Booklet” prepared by each engineering department. Students receive practical knowledge and hands-on experience in an industrial setting.

INDR 343 – Stochastic Models
Credits: 3
Prerequisites: (ENGR 200 and INDR 262) or consent of the instructor
Introduction to inventory management, deterministic economic quantity models, and extensions. Stochastic continuous-review and periodic-review models. Markov chains and Markov processes. Introduction to queueing systems and the Poisson process. Markovian queues, networks, and management of queueing systems. Markov decision models and applications. Probabilistic dynamic programming and algorithmic solution methods.

INDR 363 – Mathematical Programming
Credits: 3
Prerequisites: INDR 262 and INDR 201
Introduction to modeling with integer variables and integer programming; network models, dynamic programming; convexity and nonlinear optimization; applications of various optimization methods in manufacturing, product design, communications networks, transportation, supply chain, and financial systems.

INDR 371 – Operations and Facilities Design
Credits: 3
Prerequisites: INDR 262 or consent of the instructor
Facilities design process; strategic facilities planning, product, process, and schedule design, flow, space, and activity relationships, personnel requirements; material handling principles, equipment, unit load concept; facility layout, types, procedures, computer-aided tools; warehousing, order picking, automated storage/retrieval systems; quantitative models for facilities planning; evaluating, selecting, preparing, presenting, implementing, and maintaining the facilities plan.

INDR 344 – Modeling and Simulation
Credits: 4
Prerequisites: INDR 252 or consent of the instructor
Introduction of simulation models to analyze the behavior of complex stochastic systems. Modeling time and randomness, model validation. Generation of stochastic inputs, random variate generation. Implementation of models arising from case studies via simulation languages and software. Output analysis, variance reduction techniques. Monte Carlo and Quasi Monte Carlo Methods.

INDR 372 – Production Planning and Control
Credits: 3
Prerequisites: (INDR 262 and INDR 343) or consent of the instructor
Quantitative models for decision-making with focus on tactical and operational decisions in manufacturing environments. Aggregate planning, inventory control, forecasting, project management, production scheduling, manpower and capacity planning, location and layout planning, manufacturing resource planning (MRP), and just-in-time (JIT) systems.

INDR 391 – Summer Practice II
Credits: 0
Prerequisites: (INDR 291 or ENGR 291) and ACWR 106-102-103-104-105-107
A minimum of 20 working days of training in an industrial summer practice program after the completion of third year. The training is based on the contents of the “Summer Practice Guide Booklet” prepared by each engineering department. Students receive practical knowledge and hands-on experience in an industrial setting.

INDR 481 – Information Systems
Credits: 3
Introduction to technological and conceptual aspects of information systems; data and information modeling systems, design and analysis of modular information systems, workflow modeling and project management methodology, models for information systems process development and implementation, post-implementation of IT systems, information systems examples including materials requirement planning, enterprise resource planning, and supply chain management.

INDR 491 – Industrial Engineering Design I
Credits: 4
A capstone design course where students apply engineering and science knowledge in an industrial engineering design project proposed by companies from different sectors. Development, design, implementation, and management of a project in teams under realistic constraints and conditions. Emphasis on communication, teamwork, and presentation skills.

SCEN Group (At least 1 of the below courses)

CHEM  104 – CHEMISTRY FOR ENGINEERING
Units: 3.00
Basics of general chemistry and introduction to quantum mechanics including chemical bonding, molecular structure, states of matter and phase transitions, intermolecular interaction, chemical equilibrium, thermodynamics/thermochemistry, acid-base equilibria, materials chemistry, and spectroscopy.

MBGE  411 – GENOME ANALYSIS & BIOINFORMATICS
Units: 3.00
Prerequisite: MBGE 101 or MBGE 200 or CHBI 300
Comprehensive introduction to the field of genomics and bioinformatic tools necessary for analyzing and interpreting genomic data. Collection and storage of sequence information. Investigation of complex biological processes using genomic data at various levels (DNA, mRNA, and protein). Next generation sequencing technologies and sequence data formats, assembly and mapping of raw sequence data, gene prediction and annotation, transcriptomics, functional genomics, genome evolution, genome-wide profiling, phylogenomics, and population genomics.

MATH  103 – INTRODUCTION TO ABSTRACT MATHEMATICS
Units: 3.00
Sets; logic and implications; proof techniques with examples; mathematical induction and well-ordering; equivalence relations; functions; cardinality; countable and uncountable sets.

MATH  303 – APPLIED MATHEMATICS
Units: 3.00
Prerequisite: MATH 204 or consent of the instructor
Review of vector calculus; Fourier series and Fourier transform; Calculus of functions of a complex variable.

MATH  304 – NUMERICAL METHODS
Units: 3.00
Prerequisite: MATH 107 or consent of the instructor
Solutions of nonlinear systems and unconstrained optimization problems; direct methods for linear systems; eigenvalue problems; polynomial interpolation; least squares problem; numerical differentiation and integration; methods for the initial value problem; Fourier transform.

MATH  305 – NUMERICAL ANALYSIS
Units: 3.00
Prerequisite: MATH 107 or consent of the instructor
Fixed point iteration and Newton’s method for nonlinear equations, direct solution of linear systems and the least squares problem, symmetric positive definite and banded matrices, systems of nonlinear equations, the QR algorithm for the symmetric eigenvalue problem, Lagrange and Hermite polynomial interpolation, polynomial approximation in the infinity norm and the Chebyshev polynomials, approximation in the 2 norms and the orthogonal polynomials, numerical differentiation, Newton-Cotes and Gaussian quadratures for numerical integration.

MATH  320 – LINEAR ALGEBRA
Units: 3.00
Prerequisite: MATH 107 or consent of the instructor
Finite-dimensional real and complex vector spaces, bases of a vector space, linear maps, dual spaces, quadratic forms, self-adjoint and unitary transformations, eigenvalue problem, the canonical form of a linear transformation, tensors, and applications.

MATH  401 – COMPLEX  ANALYSIS
Units: 3.00
Prerequisite: MATH 301 or consent of the instructor
Complex numbers and functions; exponential and trigonometric functions; infinite series and products; limits, continuity and derivatives of complex functions; Cauchy’s theorem; Taylor and Laurent series; conformal mapping.

MATH  404 – GRAPH THEORY
Units: 3.00
Fundamental concepts in graph theory; trees; matchings in graphs; connectivity and planarity; the colorings of graphs and diagraphs; Hamilton cycles; matroids.

MATH  407 – COMBINATORIAL ANALYSIS
Units: 3.00
Problems of enumeration, structure, and optimization in such finite or discrete systems as graphs, matroids, partially ordered sets, lattices, partitions, codes, and block designs.

MATH  408 – GAME THEORY
Units: 3.00
Games in extensive form; pure and behavioral strategies; normal form, mixed strategies, equilibrium points; coalitions, characteristic-function form, imputations and solution concepts; related topics and applications.

PHYS  201 – MECHANICS
Units: 3.00
Prerequisite: (PHYS 101 and MATH 204) or consent of the instructor
Review of vectors and matrices, orthogonal transformations; numerical simulations and animations of mechanical systems, kinematics and dynamics of particles; Newton’s laws of motion; conservation laws; oscillations; central forces; orbits and scattering in a central force field; planetary motion; non-inertial reference frames; potential theory; the two-body problem.

PHYS  205 – GENERAL PHYSICS III
Units: 4.00
Prerequisite: PHYS 101 or consent of the instructor
Periodic motion, fluid mechanics, mechanical waves, sound and hearing, temperature and heat, thermal properties of matter, the first law of thermodynamics, the second law of thermodynamics. Lab component.

PHYS  206 – GENERAL PHYSICS IV
Units: 4.00
Prerequisite: PHYS 102 or consent of the instructor
The nature and propagation of light, geometric optics, and optical instruments, interference, diffraction, relativity, photons electrons, and atoms, the wave nature of particles, quantum mechanics, atomic structure, molecules and condensed matter, nuclear physics, particle physics, and cosmology. Lab component.

PHYS  403 – SOLID STATE PHYSICS
Units: 4.00
Prerequisite: PHYS 102 or consent of the instructor
Elementary crystal structure; the reciprocal lattice; lattice dynamics and phonons; thermal properties of materials; electron gas; Fermi-Dirac statistics and the Fermi surface; band theory, semiconductor physics, and properties, semiconductor devices.