The multi-disciplinary four-year BS in Engineering Sciences offered by the Zaven and Sonia Akian College of Science and Engineering (CSE) is designed for students who are interested in a broad-based general engineering degree. The program incorporates course work in mechanical and electrical engineering, computer science and engineering design while being strongly rooted in natural and physical sciences and mathematics. The program aims to explore synergies among science, technology, engineering and mathematics (STEM) in enabling students to understand a multitude of complex systems and address the challenges of Armenia, the region and the world.
Making use of synergies with AUA’s Entrepreneurship and Product Innovation Center (EPIC), the BS in Engineering Sciences program accentuates innovation and creativity, fostering an entrepreneurial disposition in graduates. The program also underscores effective oral and written communication skills to help graduates convey ideas from the discipline to become change-agents and leaders.
Graduates of the program will be well prepared for employment in a wide range of sectors requiring analytical and quantitative skills as well as advanced studies in a wide variety of academic disciplines, such as mechanical, electrical, and systems engineering, computer science and robotics.

The BS in Engineering Sciences is offered as part of AUA’s liberal arts education.  Program-wide and university-wide goals have been designed to ensure that AUA’s graduates become not only specialists in their fields, but also develop into well-rounded individuals, able to think critically and creatively, to learn independently, to understand different thinking traditions, to work collaboratively, and to interact with people from different cultures and disciplines.

 

Engineering Sciences Major Core 

Calculus: Single Variable – This introductory calculus course for engineering students covers differentiation and integration of functions of one variable, with applications. Topics include Concepts of Function, Limits and Continuity, Differentiation Rules, Application to Graphing, Rates, Approximations, and Extremum Problems, Definite and Indefinite Integration, The Fundamental Theorem of Calculus, Applications to Geometry: Area, Volume, and Arc Length, Applications to Science: Average Values, Work, and Probability, Techniques of Integration, and Approximation of Definite Integrals, Improper Integrals, and L’Hôspital’s Rule. Instructor-led class time including problem sets and discussions.
Calculus: Multi Variable – This calculus course builds on topics covered in Calculus: Single Variable, encompassing vector and multi-variable calculus. Topics include power series and their expansions, partial differentiation and multiple integration with applications, vectors, and vector-valued functions. Line and surface integrals are introduced along with their application to concepts of work and flux, and studied by means of the theorems of Green, Gauss, and Stokes. Instructor-led class time including problem sets and discussions.

Linear Algebra and Ordinary Differential Equations – This course introduces students to linear algebra and ordinary differential equations (ODEs), including general numerical approaches to solving systems of equations. Topics include linear systems of equations, existence and uniqueness of solutions, Gaussian elimination, initial value problems, 1st and 2nd order systems, forward and backward Euler, and the Runge-Kutta method (RK4). The course also covers eigenproblems: eigenvalues and eigenvectors, including complex numbers, functions, vectors and matrices. Instructor-led class time including problem sets and discussions.

Probability and Statistics – The topics covered in this introductory course include: axioms of probability; conditional probability, independence; combinatorial analysis; random variables and distributions; expectation, variance, covariance; transformation of random variables; limit theorems, the law of large numbers, the central limit theorem; Markov chains; applications; statistical estimation; correlation, regression; hypothesis testing, maximum likelihood estimation, Bayesian updating; applications. Instructor-led class time including problem sets and discussions.

Chemistry – This course introduces students to principles of chemistry. Topics include atomic theory, periodic properties, stoichiometry, nomenclature, bonding, physical properties of states of matter, solutions, kinetics, equilibrium, acid-base reactions, metathesis reactions, redox reactions, thermodynamics, electrochemistry, and chemical properties of selected classes of compounds. Instructor-led class time including discussions and problem sets.

Chemistry Lab – Hands-on laboratory course to accompany Chemistry. Students will conduct experiments in support of the topics covered in Chemistry.

Mechanics – This course introduces students to classical mechanics. Topics include: space and time; straight-line kinematics; motion in a plane; forces and static equilibrium; Newton’s laws; particle dynamics, with force and conservation of momentum; angular motion and conservation of angular momentum; universal gravitation and planetary motion; collisions and conservation laws; work, potential energy and conservation of energy; vibrational motion; conservative forces; inertial forces and non-inertial frames; central force motions; rigid bodies and rotational dynamics. Instructor-led class time including discussions and problem sets.

Mechanics Lab – Hands-on laboratory course to accompany Mechanics. Students will conduct experiments in support of the topics covered in Mechanics.

Electricity and Magnetism – This course introduces students to topics related to electricity and magnetism, including Coulomb’s law, electric and magnetic fields, capacitance, electrical current and resistance, electromagnetic induction, light, waves, quantum physics, solid state physics, and semiconductors. Instructor-led class time including discussions and problem sets.

Electricity and Magnetism Lab – Hands-on laboratory course to accompany Electricity and Magnetism. Students will conduct experiments in support of the topics covered in Electricity and Magnetism.

Discrete Math – This is an introduction to discrete mathematics and discrete structures. The course examines topics including: propositional logic; Boolean algebra; introduction to set algebra; infinite sets; relations and functions; recurrences; proof techniques; introduction to number theory; elementary combinatorics and graph theory; applications to computer science. Students will learn to apply discrete numerical methods to solve problems which arise in computational sciences. Instructor-led class time including problem sets and discussions.

Introduction to Programming – This course covers the fundamental elements of imperative programming languages (variables, assignments, conditional statements, loops, procedures, pointers, recursion), simple data structures (lists, trees) and fundamental algorithms (searching, sorting). Instructor-led class time including problem sets and discussions.

Data Structures and Algorithms – The course explores topics including: basic object-oriented programming principles; linear and non-linear data structures – linked lists, stacks, queues, trees, tables and graphs; dynamic memory management; design of algorithms and programs for creating and processing data structures; searching and sorting algorithms. Students are required to complete programming projects in which they design, analyze, and develop complex data structures in at least one programming language. Instructor-led class time including problem sets and discussions.

Computer Organization – Functional organization and operation of digital computers. Coverage of assembly language; addressing, stacks, argument passing, arithmetic operations, decisions, macros, modularization, linkers, debuggers. Device drivers will be considered. Instructor-led class time including problem sets and discussions.

Engineering Statics – This course introduces students to fundamental engineering principles such as forces, moments, couples, resultants of force systems, equilibrium analysis and free-body diagrams, analysis of forces acting on members of trusses, frames, shear-force and bending-moment distributions, Coulomb friction, centroids and center of mass, and applications of statics in design. Instructor-led class time including problem sets and discussions.

Engineering Dynamics – This course engages students in formulating and solving problems that involve forces that act on bodies which are moving. Topics include kinematics of particles and rigid bodies, equations of motion, work-energy methods, and impulse and momentum, translating and rotating coordinate systems. Instructor-led class time including problem sets and discussions.

Circuits – Introductory course in fundamental electrical circuit theory as well as analog and digital signal processing methods currently used to solve a variety of engineering design problems. Circuit and system simulation analysis tools are introduced and emphasized. Topics include basic concepts of AC/DC and digital electrical circuits, power electronics, linear circuit simulation and analysis, op-amp circuits, transducers, feedback, circuit equivalents and system models, first order transients, the description of sinusoidal signals and system response, analog/digital conversion, basic digital logic gates and combinatorial circuits. Instructor-led class time including problem sets and discussions.

Circuits Lab – Hands-on laboratory course to reinforce concepts covered as well as provide system-level understanding. Students will conduct experiments in support of the topics covered in Circuits.

Embedded Systems – This course introduces students to the unique computing and design challenges posed by embedded systems. Students will solve real-world design problems using small-scale and resource-constrained platforms. Examples will be drawn from combined hardware and software systems and basic interactions between embedded computers and the physical world. Emphasis is placed on interfacing embedded processors with common sensors and devices (e.g. temperature sensors, keypads, LCD display, SPI ports, pulse width modulated motor controller outputs) while developing the skills needed to use embedded processors in systems design. Instructor-led class time including problem sets as well as experimentation using hardware/software equipment. Instructor-led class time including problem sets and discussions.

Signals and Systems – This course develops further understanding of principles of electrical and mechanical systems. Topics include representations of discrete-time and continuous-time signals such as Fourier representations, Laplace and Z transforms, sampling; representations of linear, time-invariant systems such as difference and differential equations, block diagrams, system functions, poles and zeros, as well as impulse and step responses and frequency responses. Examples are drawn from engineering and physics, including the realms of feedback and control, communications, and signal processing. Instructor-led class time including problem sets and discussions.

Numerical Methods – This course covers fundamentals of numerical methods in engineering. Topics include floating-point computation, systems of linear equations, approximation of functions and integrals, and numerical analysis and solutions of ordinary differential equations. Instructor-led class time including computational platforms, problem sets and discussions.

Computer Aided Design – Fundamentals of part design; computer-aided design tools and data structures; geometric modeling; transformations; CAD/CAM data exchange; mechanical assembly. Instructor-led class time including problem sets and discussions.

Control Systems 1 – This course synthesizes fundamental electrical and mechanical principles in the analysis and design of control systems and control systems technology. Sensors, actuators, modeling of physical systems, design and implementation of feedback controllers; operational techniques used in describing, analyzing and designing linear continuous systems; Laplace transforms; response via transfer functions; stability; performance specifications; controller design via transfer functions; frequency response; simple nonlinearities. This course is intended to be taken concurrently with Control Systems 1 Lab. Instructor-led class time including problem sets as well as experimentation in a variety of controls applications.

Control Systems 1 Lab – Hands-on laboratory course to reinforce concepts covered as well as provide system-level understanding. Students will conduct experiments in support of the topics covered in Control Systems 1.

Control Systems 2 – Building on Control Systems 1, this course engages students in more rigorous analysis in control theory. Methods include time domain modeling, trajectories and phase plane analysis, similarity transforms, controllability and observability, pole placement and observers, linear quadratic optimal control, Lyapunov stability and describing functions and simulation. This course is intended to be taken concurrently with Control Systems 2 Lab. Instructor-led class time including problem sets as well as experimentation in a variety of controls applications.

Control Systems 2 Lab – Hands-on laboratory course to reinforce concepts covered as well as provide system-level understanding. Students will conduct experiments in support of the topics covered in Control Systems 2.

Mechatronics Design – This course is to expose students to the fundamentals of mechatronic and robotic systems. Over the course of these lectures, topics will include how to interface a computer with the real world, different types of sensors and their use, different types of actuators and their use. Instructor-led class time including problem sets, projects, and discussions.

Capstone – Students will select a topic through consultations with the Program Chair and/or advisors and work on the course-long project under mentorship of the supervising instructor. Students will participate in scheduled meetings conducted by the instructor and discuss each others’ projects. At the end of the course the projects will be presented orally and the project reports submitted in writing.

 

Distribution 1

(1 course)

Distribution 2

(1 course)

Introduction to Materials Science Biotechnology
Introduction to Chemical Engineering Alternative Energy
Thermodynamics Biology
Introduction to Fluid Mechanics Bioinformatics
Data Science with R Environmental Engineering
Heat Transfer Resource Management
Machine Learning Project Management

To complete the BS in Engineering Sciences, students must complete a total of 43 courses, including 15 General Education courses, 28 ES Major Core courses, 2 Distribution requirments, and 3 Free Elective courses, in addition to Physical Education, First Aid, and Civil Defense Requirements.