| Course Code |
Course Name |
Credit Hours |
Prerequests |
|
10032100
|
Remedial English
|
0 |
|
| This is a three-hour non-credited English course offered to students who score poorly (i.e. below 50%) on the placement test. Since the major concern of this course is to improve the students’ proficiency before starting their ordinary university English basic courses and major courses taught in English, special emphasis has been placed on enhancing the students’ ability to effectively acquire the four language skills: reading, writing, listening, and speaking. Specifically, the course attempts to ensure an academically acceptable performance on the part of the students at the level of the English basic courses. Moreover, the course aims at expanding students’ vocabulary needed for various tasks. |
|
11000101
|
Islamic Culture
|
3 |
|
| This course aims to establish the concept of Islamic culture and its position among the other international cultures, its position in the Muslim life, its sources, its bases and its characteristics. It also aims to introduce the Islamic culture in faith, worship, relations, morals, and knowledge, to discuss the clash between cultures in addition to Globalization, Human Rights, Woman Rights, Democracy and other contemporary issues. |
|
11000102
|
Arabic Language
|
3 |
|
| This course aims to improve the level of students in language skills and various literary, read and absorb and express written, and oral and tasted literary, through texts flags authors and poets in different eras, lessons in grammar and spelling, and brief definition months dictionaries and Arab old ones the modern and how to use them. This course aims to implement the Arabic language in the areas of reading and expression of both types oral and written communication. |
|
11000103
|
English Language I
|
3 |
|
| This is a three credit-hour university-required English language course designed for students who need to work on the four skills of the language: reading, writing, listening, and speaking. The development of vocabulary and skills of comprehension are integral parts of the course. In addition, various reading strategies (making predictions, identifying main ideas, reading for details, relating information in the text to life experience) are introduced and developed through a wide range of topics for reading and writing. The course encourages a more analytical and independent approach to study and helps prepare the students for any subsequent exam preparation. |
|
11000105
|
Palestinian Studies
|
3 |
|
| The course is mandatory for university students from various disciplines, so it does provide students with knowledge and `information about the Palestinian reality and in particular the political developments of the Palestinian cause since its inception until the present day in line social and economic developments and political which constitute the main pillars for the study of the Palestinian political reality. This course aims to study Palestinian issue from its begging until present day in social, economic and political issue. |
|
11000108
|
Community Service
|
1 |
|
|
11000117
|
Leadership and Communication Skills
|
1 |
|
|
11000126
|
Introduction to Computer Science and Skills
|
2 |
|
|
11000328
|
English Language II
|
3 |
|
| Course Code |
Course Name |
Credit Hours |
Prerequests |
|
10211101
|
Calculus I
|
3 |
|
| This course covers the concepts of function, inverse function, models, limits, continuity and derivatives, the differentiation rules and their applications, related rates, linear approximation and hyperbolic functions. In addition to the mean value theorem, indeterminate forms and L' Hospital's rule, curve sketching and optimization problems. |
|
10211102
|
Calculus II
|
3 |
|
| Definite integral and its properties, limited integration, integration of compensation, the space between two curves, volumes of revolution, ways of integration (integration by parts, integration of partial fractures, integration of trigonometric functions and integration with compensation trigonometric functions), integrals ailing, the length of the curve and the area of surfaces of revolution, final sequences and series, tests of convergent series, power series, Taylor series. |
|
10211201
|
Calculus III
|
3 |
|
| Topics covered in this course include: parametric equations and polar coordinates; vectors in R2 and R3 & surfaces; vector-valued functions; partial differentiation with applications; multiple integrals. |
|
10211203
|
Principles of Differential Equations
|
3 |
|
| Topics covered in this course include: classifications and solutions of first-order ordinary differential equations with applications; higher-order and solutions; power series solutions; Laplace transforms; solutions of systems of linear differential equations. |
|
10211211
|
Principles of Mathematics
|
3 |
|
| Topics covered in this course include: logic and proofs; set theory, relations and functions; cardinality and examples on mathematical structures. |
|
10211220
|
Computer and Mathematics
|
3 |
|
| Topics covered in this course include: fundamentals of programming; algorithms, types of data and control statements, dimensions, functions and subroutines; some mathematical software with applications. |
|
10211241
|
Linear Algebra I
|
3 |
|
| Topics covered include: matrices, vectors and elementary row operations; operations on matrices; determinants and inverses of matrices; systems of linear equations and method of solutions; vector spaces, linear independence and basis; linear transformations, kernel and range; Eigen values and eigenvectors. |
|
10211321
|
Numerical Analysis I
|
3 |
|
| Topics covered in this course include: numbers, Binary, Octal and Hexadecimal number systems; floating point arithmetic, Errors, sources and types; solving nonlinear equations, direct and indirect methods in solving systems of linear equations, solving systems of nonlinear equations; approximation and interpolations, numerical integration. |
|
10211322
|
Linear Programming
|
3 |
|
| Topics covered in this course include: problem formulation; graphic solution; simplex method; duality theorem; linear sensitivity analysis and algebraic representation; transportation and assignment problems; network (PERT and CPM); game theory. |
|
10211491
|
Seminar
|
1 |
|
| This course involves discussion of characteristics of scientific thinking and its relationship with scientific research; it requires students to conduct a research on a specific topic in mathematics, and to deliver it and represent this research in a seminar for evaluation. |
|
10216201
|
Methods of Statistics I
|
3 |
|
| Topics covered in this course include: statistical data classifications and description; measure of central tendency and variability; probability concepts and rules; discrete and continuous random variables; probability distributions; the binomial and normal distributions; sampling distributions; point and interval estimations for one population mean; tests of hypotheses for one population mean. |
|
10216202
|
Methods of Statistics II
|
3 |
|
| Topics covered in this course include: sampling distributions; confidence intervals; testing hypotheses for one and two population parameters; regression and correlation; testing hypotheses for regression line parameters; analysis of variance; chi-square test and non-parametric tests. |
|
10216302
|
Probability Theory I
|
3 |
|
| Topics covered in this course include: basic concepts of probability; discrete and continuous random variables; probability distributions; the binomial, geometric, negative binomial, uniform, gamma and normal probability distributions; examination of moment generating functions; probability distributions of functions of random variables. |
|
10216343
|
Applied Regression Analysis
|
3 |
|
| This course covers simple linear regression, multiple regressions, estimation, and goodness if fit tests, residual analysis, using matrices a regression, and factor rotation and applications. |
|
10216351
|
Experimental Design and ANOVA
|
3 |
|
| Topics covered in this course include: random column design, Latin squares design, two-factors design, multi-factors comparative experiment, testing model accuracy in analysis of variance, insufficient sector model factor analysis, and multiple comparisons. |
|
10221101
|
General Physics I
|
3 |
|
| This course covers the following topics: motion in one and more dimensions, the laws of motion with an application of Newton’s laws, vector quantities, work and mechanical energy, linear momentum and collisions, and rotational dynamics |
|
10221102
|
General Physics II
|
3 |
|
| This course is a study of the following topics: electric charges; forces and fields; electric potential and electric potential energy; electrical capacitance electric elements like capacitors, resistors, and conductors; electric current and direct-current circuits; magnetic fields; magnetic force; induction; and RC and RL circuits. |
|
10221107
|
General Physics 1 Lab.
|
1 |
|
| In this lab., experiments related to mechanics mostly covered in general physics I (10221101) are performed. This includes
-Measurements
-Vectors.
-Acceleration on an inclined plane.
-The speed of sound in air
-Viscosity
-Newton’s second law
-Conservation of energy and momentum
-Rotational dynamics
-Simple harmonic motion.
-Boyle’s law. |
|
10671101
|
Principles of Programming I
|
3 |
|
| This Course begins with an introduction to computers, hardware and software and problem-solving. This Course also includes an introduction to programming using C/C++ including: I/O; expressions and arithmetic; if, while and for statements; one-dimensional arrays, string handling, functions, scope, recursion and matrices. |
|
10671102
|
Principles of Programming II
|
3 |
|
| This Course covers more advanced C/C++ Programming Features including: pointers, dynamic memory, structures, text files, binary files, classes and objects. |
|
10671210
|
Data Structure
|
3 |
|
| This Course is an introduction to the various Data Structures which use an object-oriented language, such as Java. The Course covers: lists, stacks, queues, heaps, trees, search trees, hash tables, the analysis and implementation of data structures, recursion, sorting and searching. |
|
10671212
|
Design and Analysis of Algorithms
|
3 |
|
| In this Course, students are introduced to the techniques used in the analysis of Algorithms and Design Methods: divide and conquer, dynamic programming, greedy algorithms, recursive, searching and sorting algorithms and Complexity Analysis. |
|
10671314
|
Object Oriented Analysis and Design
|
3 |
|
| This course introduces object-oriented programming concepts. The course covers: class derivation, inheritance, dynamic polymorphism, object oriented analysis and design using UML language. |
|
10671315
|
Big Data
|
3 |
|
|
10671353
|
Database Systems Design
|
3 |
|
| Students are introduced to database system concepts and architecture, data modeling using E-R Model, Relational model, Normalization, Operations on Relational model, Relational constraints and Relational Algebra, SQL-the relational database standard, security in SQL and a PL/SQL overview. Furthermore an overview of the Oracle system, Distributed databases and client-server Architecture will be provided. |
|
10671372
|
Computer Simulation
|
3 |
-
-
-
10671212 or
-
10672228 or
-
10211211 or
-
10671231
|
| This course examines simulation and queuing models, random numbers generation, statistical sampling and analysis of data, simulation languages and selected applications. |
|
10671483
|
Artificial Intelligence
|
3 |
|
| Students receive instruction on basic concepts and techniques of artificial intelligence. Emphasis is placed on problem solving methods: blind and informed search, game playing: minimax and alpha beta pruning algorithms, representation of knowledge using predicate logic, resolution, backward-chining and Prolog, forward-chaining systems, inductive learning, decision trees, neural networks, planning and reasoning under uncertainty. |
|
10671498
|
Graduate Project
|
3 |
|
| In Fourth year, students are required to make a complete investigation, analysis, programming and implementation of a selected system. The students are required to deliver a presentation and demonstrate their work in front of a 3 person committee from the department. |
|
10671499
|
Training
|
3 |
|
| 320 hours of practical training. |
|
10672224
|
Fundamentals of Artificial Intelligence
|
3 |
|
| This course will introduce the fundamental concepts and techniques used to design and build intelligent computer systems. A particular focus will be on the statistical and decision-theoretic modeling paradigm. Students will be able to build autonomous agents that can efficiently make decisions in fully informed, partially observable and adversarial environments. The constructed software agents are capable of performing intelligently by either accomplishing computation, e.g., searching, or by drawing inferences by learning from data. Students will understand what supervised machine learning algorithms are and how they can be employed in classifying handwritten digits and photographs. The techniques you learn in this course apply to a wide variety of artificial intelligence problems and will serve as the foundation for further study in any application area you choose to pursue. |
|
10672350
|
Data Warehouse
|
3 |
|
|
10672355
|
Data Mining and Machine Learning
|
3 |
|
| Course Code |
Course Name |
Credit Hours |
Prerequests |
|
10211212
|
Modern Analysis I
|
3 |
|
| Topics covered in this course include: properties of real numbers; open and closed sets; sequences; limits and continuity; differentiation; Riemann integral. |
|
10211302
|
Partial Differential Equations I
|
3 |
|
| Topics covered in this course include: the formation of a partial differential equation; methods of solutions of first order linear and nonlinear partial differential equations; methods of solutions of second order linear and nonlinear partial differential equations; Fourier series and transforms; wave equation, Laplace’s equation, potential equation, equation of an infinite wire, heat equation. |
|
10211303
|
Vector Analysis
|
3 |
|
| Topics covered in this course include: vector algebra, vector products, vectors and scalar fields; the gradient, divergence and curl theorems; line, surface and volume integrals, related theorems; curvilinear coordinates |
|
10211323
|
Operations Research I
|
3 |
|
| Topics covered in this course include: introduction to operation research; inventory models, queuing models; game theory; Markov chains; case studies. |
|
10211474
|
Combinatorics & Graph Theory
|
3 |
|
| This course focuses on graphs: simple graphs, directed graphs, components, connected components; blocks, cut-vertices, and bridges; Euler graphs; trees, planar and non-planar graphs; graph matrices and coloring. |
|
10216303
|
Probability Theory II
|
3 |
|
| This course includes review of some properties of random variables and probability distributions, multinomial distributions, distribution of order statistics, and moments and moment generating functions for some probability distributions. Limiting distributions, types of convergence and characteristic functions are also examined. |
|
10216304
|
Mathematical Statistics I
|
3 |
|
| This course provides an introduction to decision theory, risk and loss functions, unbiased estimation, efficient and maximum likelihood estimation, confidence intervals, testing statistical hypotheses, sufficient statistics, the Rao-Blackwell theorem and Rao-Cramir inequality. |
|
10216305
|
Mathematical Statistics II
|
3 |
|
| This course covers properties of point estimates, the exponential family of distributions, sufficiency and completeness, Bayesian estimation, most powerful test, sequential test, and estimation and testing hypotheses for linear models. |
|
10216371
|
Time Series Analysis
|
3 |
|
|
10631300
|
Innovation and Entrepeneurship
|
3 |
|
| This course is designed for students of the Faculty of Engineering and IT to help them be involved in creative, innovative, entrepreneurial and corporate ventures in the future. Subjects covered include: introduction to entrepreneurship & creativity; developing successful business ideas, managing and growing an entrepreneurial firm; technical and financial feasibility studies; business models; market survey; business plan preparation.Learning Outcomes: after successful completion of this course, students will be able to:1) Demonstrate a solid theoretical understanding of the innovation process, entrepreneurship and their associated management issues in the business economy.2) Find, launch and manage high growth potential new ventures by looking for and evaluating business opportunities, preparing business plans, designing and validating business models to build successful start-ups.3) Design, implement and manage a company’s innovation strategy, network or system. |
|
10671325
|
Computer Vision
|
3 |
|
|
10671371
|
Computer Graphics
|
3 |
|
| This course covers basic graphics operations and their implementations in 2 dimensions, introduction to OpenGL, devices for construction and display of computer-generated images, widowing and clipping, 2D geometric, transformation and viewing, 3D object representation, transformation and viewing. |
|
10671374
|
Digital Image Processing
|
3 |
|
| Image formats, image recognition, image extraction, image processing primitives, and image indexing. Clustering: hierarchical and non-hierarchical methods, clustering using neural networks and genetic algorithms. Classifications: nearest neighbors, neural nets, and genetic methods. Image enhancement, segmentation, measurement, Fourier analysis, image storage and retrieval. |
|
10671415
|
Social Netweork Analysis
|
3 |
|
|
10671453
|
Database Management Systems
|
3 |
|
| Students will study advanced concepts in creating and managing tables, storage access and index structure.. In addition, they will learn Distributed DB concepts, create and maintain constraints, and create views, PL/SQL block and its sections. They also learn about Triggers, functions, procedure and packages, along with Database connectivity (ODBC, OLE, and ADO), managing users. Practical tools are used to implement the different concepts. Form builder, report builder and Oracle 10g are used. |
|
10671491
|
Special Topics
|
3 |
|
| Students are introduced to advanced selected topics in different areas of computing. |
|
10672346
|
Ontology Engineering for the Semantic Web
|
3 |
|
