Academics

Academic hours: 39
ECTS: 4.5
Semester: A+B

The course is an introduction to machine learning and deep learning concepts and
algorithms. Today, Convolution Neural Networks (CNN) are in great use in many systems and are developed for classification
and regression purposes.

Subjects of this course include: supervised learning,
generalization and overfitting, optimization methods, computer vision, CNN basics, CNN architectures and current advanced topics.

The course will include lectures and seminars given by students on papers from leading scientific journals.

Academic hours: 39
ECTS: 4.5
Semester:  B

The seminar focuses on algorithmics in distributed systems and networks. The aim is to study basic topics and techniques related to design and analysis of AI algorithms in non-faulty networks, and algorithms and impossibility results in faulty networks. Within faulty networks the seminar also considers self-stabilizing systems. In addition, basic concepts concerning online algorithms and approximation algorithms in networking problems are addressed.

Academic hours: 39
ECTS: 4.5
Semester: A + B

The course is an introduction to Deep learning, concepts
and algorithms of this field of machine learning and
its implementation using advanced modern neural
networks. Subjects of this course: Introduction to python, Computer vision, neural networks, architectures, objects detection, visualization, and image classification.

Academic hours: 39
ECTS: 4.5
Semester: A + B

This lab-based course will introduce you to the mobile
software developing arena. You will get acquainted
with of the Android OS architecture and master
yourself on developing interactive and responsive
UI components for mobile devices while taking into
consideration various localization and target devices
constraints. Among other topics, we will cover layout
designs (declarative & imperative), fragments, inter and
intra communication methods within/between mobile
applications, and practice various methods to persist
app and user data. As part of the lab evaluation, you will
have the opportunity to design and develop your own
application to practice and demonstrate the course
topics.

Academic hours: 39
ECTS: 4.5
Semester: B

Students will learn various concepts in the area of Cloud
Computing, including cloud models (private, public,
hybrid), and cloud services (SAAS, PAAS, IAAS). We will
discuss the implications of using cloud computing,
from different aspects, such as the economical aspect,
maintaining data privacy, and cloud migration. The course
will also include practical assignments, developing
a web-based cloud application in a commercial
framework. The application will be implemented using
common programming languages. The application will
we deployed in a cloud environment. The course will
also include reading assignments, where the students
will analyze academic papers, addressing contemporary
issues in cloud computing research.
Completing the course, the students will be able to
build and deploy a cloud application, using commercial frameworks.

Academic hours: 39
ECTS: 4.5
Semester: A + B

The Capstone Project encompasses utilizing a variety of methods, tools and techniques in software engineering and computer science, with the intention to apply the knowledge and engineering capabilities acquired throughout the course of learning thus far. The Capstone Project includes a research component which focuses on either a theoretical area (Computer Science), technological area (engineering, innovation, etc.), or application domain. This course is the first out of two semestrial phases of the Capstone Project.

Academic hours: 39
ECTS: 4.5
Semester: A + B

The Capstone Project encompasses utilizing a variety of methods, tools and techniques in software engineering and computer science, with the intention to apply the knowledge and engineering capabilities acquired throughout the course of learning thus far. The Capstone Project includes a research component which focuses on either a theoretical area (Computer Science), technological area (engineering, innovation, etc.), or application domain. This course is the second phase of the Capstone Project, in which the outcome of the first phase is further developed, including application, implementation and evaluation of the software which was built to achieve the project’s goals.

Academic hours: 39
ECTS: 4.5
Semester: B

The seminar will provide a combination of fundamental concepts and advanced techniques in the field of artificial intelligence. A wide range of decision making problems and environments are covered in this course involving agents and multi-agent systems. Problem solving through search methods and reasoning in uncertain and constrained environments is discussed. The Markov decision problem (MDP) and Q learning are also examined. The seminars use state-of-the-art papers from leading journals.

Academic hours: 39
ECTS: 4.5
Semester: B

Tissue engineering is a key method in the practical aspects of regenerative medicine. Due to the importance of the field, it is important to expose students to existing advanced technologies. The course deals with practical aspects of culturing and monitoring animal cells, by using advanced tissue engineering methods. The course focuses on hands-on practice. The students will be exposed to common laboratory work: medium preparation and change, cells splitting and routine culture of cell lines in the lab.

During the laboratory work, students will practice tissue formation (cell differentiation) by using different types of cells seeded on various scaffolds\hydrogels: Alginate, Matrigel matrix™ and a unique GAG mimetic hydrogel. Cultured cells features will be examined by morphology and by Immunostaining using specific cells markers.

Academic hours: 26
ECTS: 4.5
Semester: B

Practice in written and spoken technical, scientific and business English. The course includes basic and essential English grammar and vocabulary, summary writing, scientific and technical reporting, meeting agenda composition, significance and execution
of minute taking, audience-directed language (register), company presentation, composition of scientific protocols, verbal and written presentation of original research/business proposals.

Academic hours: 39
ECTS: 4.5
Semester:  B

The course aim is to provide a framework of basic drug design and development, into which current and future drugs may be fitted. The difference between innovative and generic drugs will be discussed. Principles such as: methods for drug discovery, drug targets, the concept of Structure Activity Relationship (SAR) and Quantitative
Structure Activity Relationship (QSAR) and optimization of the drug interactions with the target will be studied. Those principles will be applied in two computational laboratory exercises.

Academic hours: 26
ECTS: 4.5
Semester: A + B

Basic concepts of Immunology. The Innate and Acquired immune systems. Cells and tissues of the immune response. Antibody genetics and structure. Antibody classes and their specific functions. The T-cell receptor, its recognition of self and non-self antigens. The Major Histocompatibility Complex (MHC), its recognition of antigens and cooperation with the T-cell receptor. Humoral and cellular immunity. Cytokines. Mechanism of immune reactions against pathogens and tumor-specific antigens. Regulation of the immune response and autoimmunity.

Academic hours: 65
ECTS: 4.5
Semester: A + B

Introduction. Hydrostatics: manometers, forces on immersed bodies. Fluid dynamics: Integral conservation laws, Bernoulli equation, differential conservation Laws, Navier-Stokes and Euler equations. External flows around immersed bodies: boundary layers, potential flow, lift, drag, wing profiles. Internal flows: Laminar flow in ducts and pipes, turbulent flow in pipes. Flow measuring devices. Pumps. Dimensional analysis and similarity. Introduction to compressible flow.

Academic hours: 70
ECTS: 4.5
Semester:  B

This course is an overview of mechatronic systems. The students study principles of microcontroller, Microcontroller programing, Digital and analog I/O, Theory of measuring systems, Sensors for measuring: force, displacement, temperature, acceleration, etc.

Actuators: DC brush and brushless motors, stepper motors, modeling a position control system, introduction to signal processing, design and implementation of digital position controller, and autonomous mechatronic system. The course includes a laboratory segment.

Academic hours: 39
ECTS: 4.5
Semester:  B

The course is an introduction course to the field of micro mechanical systems (also known as Micro Electro Mechanical Systems-MEMS). Micro system is characterized by it’s micro scale dimension (1 micron = 10-6 m) and by the potential of manufacturing mechanical and electronic components on the same substrate. The aim of the course is to expose the student
to the field of modeling and fabrication of micro mechanical systems (MEMS). The course deals with applying engineering principles in order to obtain the desired mechanical and other physical properties of micro systems. The Course will consider the following subjects: Int. to modeling and fabrication of micro
systems. Micro beams and mechanical springs that determines the mechanical stiffness of floating micro systems. Electrostatic Micro sensors and micro actuator. Piezo-electric and Piezo-resistive micro sensors and actuator. Micro Thermal sensors and actuators. Micro fabrications processes such as: lithography, deposition and etching.

Academic hours: 39
ECTS: 4.5
Semester: A + B

The course gives the student basic understanding of the following subjects:

• Practical aspects of materials engineering and their implementation.
• Acquaintance with various manufacturing processes starting with selection and ordering materials to final product manufacturing.
• Exposure to techno-economic considerations and production in a competitive environment.
• Planning manufacturing operations and acceptance testing.

Academic hours: 52
ECTS: 4.5
Semester:  B

The main objective is to become acquainted
with various aspects related to “Industry
4.0”, including efficiency and productivity,
process chains, optimization, sensors and
automation, sustainability, biologicalisation,
energy and resources, digitization, and the
use of data in the world of new manufacturing
systems, conventional processes, and advanced
technologies like AM, EDM, ECM, Waterjet, and
Laser in industry. In addition, students will
acquire up-to-date knowledge on industrial and
scientific developments, new materials, powder
materials, composite, and micro-machining

Academic hours: 52
ECTS: 4.5
Semester:  B

The course is focus on the approximation of real-valued continuous functions by some simpler class of functions, such as algebraic polynomials.

Some of the topics that will be investigated are:

• Chebyshev Polynomials
• Least square problems
• Projection methods
• Interpolation (for example: Lagrange, Chebyshev, Hermite)
• Remez’s algorithm
• Padé approximant

The above and more related topics will be practiced Chebfun (an open-source package for computing).

Academic hours: 52
ECTS: 4.5
Semester:  B

This course is centered around acquiring knowledge of algebraic structures, including groups, rings and fields. These areas are central to mathematics and are widely
used in applications, especially in computer science.

Academic hours: 52
ECTS: 4.5
Semester: A + B

The subject matter of this course encompasses the fundamental principles and relevant techniques for designing continuous-time SISO LTI control systems that satisfy practically relevant system performance specifications. Topics of the course are: introduction and foundations, Feedback control fundamentals, Loop transfer function fundamentals, Linear SISO systems, and tracking design with uncertain plants. Expected outcome of the course: The student is able to design continuous-time SISO LTI control systems that satisfy practically relevant system performance specifications in frequency domain.

Academic hours: 84
ECTS: 4.5
Semester: A + B

Basic properties of the human visual system. Pixel. Computer presentation of the Gray and RGB images as arrays. Creating a set of synthetic test images by using C and C++. Contrast and Brightness. Pixel-to- Pixel operations: Contrast stretch, Automatic Min-Max  contrast stretch, Histogram Equalization. Usage of LUT and pointers for fast implementation of pixel-to-pixel operations. Geometrical Transformations: scaling, rotation, affine Transform. Image registration. Median filtration. Filtration by convolution. Gaussian filter.

Usage of FFT for Image Processing. Unsharp Masking. Edge detectors. Usage of MATLAB for fast prototyping Image Processing systems. Design and properties of digital camera. In the frames of the course, laboratory, students implement a selection of the Image Processing algorithms by using Visual Studio (C, C++, C#, .NET).

Academic hours: 39
ECTS: 4.5
Semester:  B

Basic analog and digital signals. Examples of medical signals (ECG, EEG, EMG, ERG, PPG). “Arduino Due” board as software defined signal generator controlled by UART command. “EasyStart Kit – PIC32MX7” board as fast prototype board for RT-DSP algorithms test.

Practical aspects of the signal’ acquisition by using ADC: pre-amplifiers, anti-aliasing filters, usage of timers and interrupts. Usage of TFT screen to present graphs of the signals and textual information. Basic DSP algorithms and their practical implementation: filtration by convolution and by using FFT, normalized correlation, autocorrelation, median filtration. In the frames of the course “Arduino Due” board and “EasyStart Kit – PIC32MX7” board are used to create working prototypes of RT-DSP systems: “Spectrum Analyzer”, “Medical signals smart monitor”, “Filtration of audio signals” and others.

Academic hours: 78
ECTS: 4.5
Semester: A + B

Analog CMOS integrated circuits design focuses on the basic building blocks including current source/mirror, single stage amplifiers, differential stage amplifier. The lab experiments involve hands-on design using state of the art CAD tools. Lectures complement the experiments providing theoretical background. The course follows the design cycle: from specification definitions, through architecture selection and basic design, to fine-tuning providing precise simulations. Simulation employing CAD tools of performance parameters such as gain, frequency response, stability, voltage span, operating point, slew rate and offset. To summarize the course, the students will be given independent design tasks (mini- projects) to implement the techniques studied.

Academic Hours: 52
ECTS: 4.5
Semester: A + B

The subject matter of this course covers two distinct but interlinked areas of knowledge or expertise: dynamical system modelling and numerical simulation of dynamical systems. The students will learn to derive mathematical models by applying the ‘law of conservation’ to various common processes with lumped parameters. The students will analyse the transient behaviour of these models in a laboratory type environment, where they will use numerical simulation methods to solve a model’s non-linear state differential
equations.

Academic hours: 78
ECTS: 4.5
Semester: A + B

This course provides an introduction to micro-processor based systems, inside architecture of 16 bit processor (Intel 8086). Principles of micro-processor programming in Machine Code, Assembly 8086 language and Modular programming. Principle operation of RISC and CISC processors. Programing for Windows OS, based on DLL files   Advanced architecture of modern processors “Intel 32bit”, Pentium4- dual core, Pentium– pro and inside architecture of “Intel 64”, Itanium. Fundamentals of development of a micro-processor based system, Pentium- Main Memory Organization, Virtual Memory, Paging Mechanism, Cache Memory Organization.  Principles of serial communication, RS-232, USB. Detailed studies of computer I/O and interrupt techniques, timers, parallel and serial interfaces. Laboratory activities provide the student with experience in developing the hardware and software required to incorporate microprocessors into systems in ASM86 language.    PC peripherals including – keyboard, screen, drives, serial port and mouse.

Academic hours: 52
ECTS: 4.5
Semester: A + B

Based on prior knowledge from previous courses, learn data structures and advanced algorithms used in engineering and electrical engineering in particular. Covering complexity costs, general search and sort algorithms, strings and different data structures and algorithms utilizing these structures. Advanced data structures: trees, graphs and algorithms like minimum path, spanning trees and more. Pattern matching and text compression, greedy algorithms.

Academic hours: 39
ECTS: 4.5
Semester: A + B

Discrete time signals and systems. Energy and power signals. Classification of digital systems: static/dynamic, time-variant/time-invariant, linear/non-linear, causal/non-causal and BIBO stable/non BIBO stable. LTI systems and convolution in discrete time. Stability and causality of an LTI system. Linear difference equations with constant coefficients. Zero Input Response (ZIR) and Zero State Response (ZSR). General and particular solutions to homogeneous difference equations. General and particular solutions to nonhomogeneous difference equations. The bilateral Z transform: definition, Region of Convergence (ROC), properties, well-known transform pairs. The inverse Z transform: definition, three methods of calculation, the importance of the ROC. Transfer function of an LTI system. Rational transfer functions, poles and zeros, pole-zero plots. Realness, stability and causality of an LTI system in Z domain. The Discrete Time Fourier Transform (DTFT): definition, properties, well known transform pairs, examples of application.

Academic hours: 52
ECTS: 4.5
Semester: A + B

Python language for quick and easy development of algorithms and programs:
in this course, you will learn an Object Oriented Programming language, based on the C language. Data structures used in the language, input/output, modules, packages,
special libraries, GUI, advanced material,
packaging, version control system.

Academic hours: 52
ECTS: 4.5
Semester: A + B

The course will provide the concepts in the Object Oriented Paradigm, and will go over practical tools used for Object Oriented Programming. The topics of the course will include the following concepts: abstract data types (ADT), overloading, encapsulation, classes, objects, Inheritance, multiple inheritance, polymorphism, generic programming, casting and more. We will also discuss practical programming skills such as efficient programming, libraries, and top-down design.

Academic hours: 39
ECTS: 4.5
Semester: A + B

This is a basic course in digital signal processing covering major topics of sampling
and reconstruction of analog signals, the DFT and FFT transforms for spectral
analysis, digital filters and digital filter design. The student is required to know and be
able to use the continuous time and discrete time Fourier transforms, the Laplace and
Z transforms prior to studying this course

Academic hours: 52
ECTS: 4.5
Semester: A + B

MATLAB programming applications,
advantages and disadvantages, MATLAB
working environment. MATLAB coding
fundamentals: matrix programming, data
types, loops and control statements, writing
scripts and functions, efficiency considerations
of coding. Matrix calculations: transposing
and inverting matrices, solving linear equation
systems, finding eigenvalues and eigenvectors,
calculating trace and determinant. Solving
equations with symbolic variables, finding
analytic solutions to differential equations,
analytic transforms. Reading from files
and writing to files, file system operations.
Plotting graphs in MATLAB. Statistical processing of data in MATLAB: calculating
standard deviation, variance, co-variance and correlation, calculating histograms, linear and polynomial regression. Working with audio signals: reading and writing, playing, recording, practical and ideal filtering, generating synthetic signals. Reading and writing image files, basic operations on images. Applications of image processing:
contrast and brightness adjustment, Look-Up Tables (LUTs), filtering and noise removal, sharpening, edge detection, binarization.
Graphical User Interface (GUI) in MATLAB:
writing applications.

Academic hours: 52
ECTS: 4.5
Semester: B

Black body radiation, other light sources, discharge light sources, emission spectral lines, monochromatic sources, and broad sources, fluorescent sources, optical fluorescence and optical phosphorescence, excitation methods and mechanisms, Stocks rule in fluorescence and symmetry between fluorescence spectrum and absorption spectrum, laser types (solid state lasers, gaseous lasers, and laser diode).
Temporal and spatial coherence, lasers principles, spontaneous and stimulated emission, Einstein coefficients and relations between the coefficients, absorption and gain, two-level laser system, population inversion, three and four-level laser systems, excitation mechanisms for different laser schemes. Laser oscillator and threshold conditions, saturation and steady state conditions, optical output power and dependence on pump power, design of optical output power and relations with output mirror reflectivity. Optical resonators, longitudinal and transverse modes, design of the optical resonator and stability, single-mode selection and etalon inside the resonator, laser pulses, generation of laser pulses by Q-switching method and by phase locking method. Laser types – solid state laser, gas laser, laser diode, and pump methods. Laser applications: communications, target detection, material processing, nuclear fusion and others according to time availability.

Academic hours: 39
ECTS: 4.5
Semester: B

This course covers the basic principles of optical imaging systems. Starting from the fundamentals of the diffraction theory of light, the main features, limitations, and engineering aspects of imaging systems are covered. Topics include diffraction-limited imaging, optical modulation function and modulation contrast function, contrast, limited resolution and target acquisition, and noise-limited imaging and target acquisition.
In addition, the effects of atmosphere, turbulence, and motion on image quality are
treated. Furthermore, the structure and main
characteristics of imaging devices are covered.
In the practical sessions, relevant problems
on imaging systems characterization, analysis
and design are addressed. The course includes theoretical problems for homework and numerical tasks.

Academic hours: 39
ECTS: 4.5
Semester: A + B

This course covers specific aspects that put Marketing at the leading edge of the modern firm’s activities: understanding customer’s needs and designing a comprehensive approach aiming to fulfill these special needs. The students will be exposed to the basic principles, perspectives, concepts, theories and models that have been crystallized into the contemporary science of Marketing.

Academic hours: 39
ECTS: 4.5
Semester:  B

This course is about integrating three concepts in a real-world context: problem-solving, creativity, and modeling. Problem-solving is a critical skill to develop and nurture. Not to mention creativity that due to the increasing complexity of challenges has been becoming a necessity rather than an advantage. To fully utilize the two in a systematic way, modeling is adopted. Via real-world case studies, we will identify, formulate, analyze,
and validate models to solve the challenges stemming from these case studies. Modeling approach will be the vehicle through which we capture the essence of the dynamics of the major problem at hand and creativity will aid in developing and soliciting innovative solutions at the various stages of the problem-solving process.
Advanced Excel will be the platform via which these models will be developed.

Academic hours: 39
ECTS: 4.5
Semester:  B

Behavioral science is a branch of the science, which is concerned with the study of human behavior. Behavioral science looks at individuals and their behavior along with the behavior of societies and groups, and processes which can contribute to specific behaviors. Learning behavioral science is an important part of becoming team or project manager. More and more, professional
and organizations are explicitly endorsing the necessity of engineers being skilled and well trained in these areas. This course will focus on human personality, motivation and other work attitudes, learning, perception, stereotypes and discrimination, burnout and stress. The theories and insights of major studies will be discussed, while emphasis their relevancy to organizations and
industry.

Academic hours: 26
ECTS: 4.5
Semester: A

This course is open to students of electrical, mechanical, software, biomedical and industrial engineering, and is designed to provide them with platforms to develop skills in interdisciplinary teamwork, lateral thinking, problem-solving, and communication with each other, health personnel, and with the community. Thus, class discussion and work in the community form an essential part of learning and assessment on the course. In addition, students are encouraged to take a broad world view in terms of the benefits to communities of functioning and well-maintained engineering projects (the bigger picture for sustainable projects) while at the same time honing memory skills and the attention to detail necessary in all engineering tasks.

Academic hours: 26
ECTS: 4.5
Semester: B

This course is an online course entitled Embracing Diversity that targets undergraduate and graduate students, and aims to expose students to diversity in four modules:

1. Multiculturalism
2. Disability and Accessibility
3. Facial Appearance
4. Gender and Sexual Orientation

Students will be exposed to diversity’s different dimensions using diverse technological tools.