Course descriptions

Object oriented analysis, design, and advanced programming concepts. Topics include: polymorphism, abstract classes, interfaces, exception handling, graphical user interface, and modelling notations.

Introductory course in digital logic and its specification and simulation. Number systems. Binary arithmetic. Boolean algebra. Combinational logic design. Sequential logic design (controllers). Data Path components (e.g. Registers, adders, register files , etc.). Memory components (e.g. RAM, ROM). Register transfer level (RTL) design.

Practicing advanced problem solving techniques: arrays, stacks, queues, strings, sorting, arithmetic, algebra, combinatorics, number theory, backtracking, geometry, graphs algorithms and traversals. Introduction to dynamic programming, preparing students majoring in computer science for international and regional ACM programming contests.

Computer architecture and organization. Topics include performance evaluation, instruction, set architecture, data path, control unit, pipelining, memory hierarchy, storage, and other I/O topics.

Introduction to systems programming in Unix/Linux environment. Topics include scripting, libraries, utilities, development tools, piping, binary files, exception handling, command-line arguments, and symbolic debugging.

Exploration of the Unix operating system, including its tools and utilities for program development, such as makefile, piping and redirection, shell scripts, regular expressions, and symbolic debuggers. In addition, this course explores advanced features of the C programming language, including various file processing, command-line and variable arguments, exception handling, and generic interfacing.

Introduction to Data Science. Topics include data acquisition, data management, data preparation and integration, data analysis, model development and deployment, and visualization.

This course introduces discrete structures. Topics include: basic logic, sets, relations, functions, proof techniques, counting methods, recursion, trees and graphs.

Introduction to web development. Topics include client/server side scripting, dynamic websites, web services, database connectivity, security, and authentication.

Design & analysis of recursive and non-recursive algorithms. Topics include asymptotic analysis of algorithm efficiency, algorithm design techniques (e.g. divide-and-conquer, dynamic programming, greedy approaches) and their applications to computational problems, and introduction to parallel algorithms.

Principles of programming language design. Specification of syntax and semantics. Underlying implementation of block structured languages. Dynamic memory allocation for strings, lists and arrays. Imperative versus applicative programming. First order logic and logic programming. Lambda calculus and functional programming languages. Modern programming languages.

In-depth study of object-oriented design patterns. Topics include: creational patterns, structural patterns, and behavioral patterns. Pattern's intent, motivation, applicability, participants, collaborations, consequences, and implementations.

Introduction to software engineering. Topics include software development life cycle, software processes, requirements engineering, software architecture and design, software testing, software evolution, and software modeling using UML.

Introduction to modern business analysis. Topics include: planning and monitoring, elicitation, requirements, analysis, solution assessment and validation, requirements management and communication, business problems identification, business cases development and plans for achieving effective solutions.

Fundamentals of Database Management Systems. Modern database models. Basic database management concepts. Query languages. Relational algebra and relational calculus. Database design through normalization. Development experience in a team environment.

Introduction to mobile application development. Topics include creating and deploying mobile applications, development approaches, programming languages, frameworks, application architecture, event-driven programming, model-view-controller, user interface and usability.

Introduction to visual representation methods and techniques for increasing the understanding of complex data. Topics include: human visual perception, visualization design principles, interactive visualization techniques, and application of visualization in analyzing complex data from various fields.

Introduction to machine learning principles, algorithms and applications. Topics include regression, classification, clustering, artificial neural networks and model evaluation.

Internship in computer science provides students with an opportunity to integrate theory and practice in a work setting. The course helps students to grow professionally and intellectually. It also sharpens their communication and teamwork skills. Enrolled students are required to complete a minimum of 150 working hours at approved organizations.

Introduction to eCommerce. Topics include electronic data interchange, digital currency, electronic catalogs, telecommunications infrastructure, data warehousing, software agents, storage retrieval, cryptographic techniques, and different levels of security.

Introduction to user interface design principles and techniques. Topics include user and task analysis, interaction design, interaction elements and styles, design patterns, visual communication, prototyping, and evaluation of different user interfaces.

Techniques for software validation and verification. Topics include: concepts of software quality (metrics, assurance, planning & implementation, process standards, validation, verification, reviews, walkthroughs and inspections). Software testing process and techniques at different levels. Validating test data.

Introduction to software maintenance and re-engineering. Topics include evolution and maintenance models, re-engineering, legacy information systems, impact analysis, refactoring, program comprehension, principles of reuse and reverse engineering, approaches, and tools used to extract information from existing software systems.

Principles and techniques for designing and implementing a compiler. Topics include lexical analysis, parsing techniques, syntax-directed translation, intermediate languages, and code generation.

Survey of artificial intelligence techniques. Topics include search, logic, knowledge representation, reasoning with uncertainty, learning, and other AI techniques.

Introduction to digital image processing. Topics include Digital image fundamentals, intensity transformations, and spatial filtering, filtering in frequency domain, Image restoration and reconstruction, Color image processing, Image compression, and Image segmentation.

The senior capstone course provides computer science students the opportunity to employ knowledge gained from courses throughout the curriculum to develop a software solution to a real-world problem from conception to completion. Students work in teams to develop software applications. Advanced methods related to requirements analysis, software design, project management, documentation and testing, programming techniques, and database designs will be applied on an incremental basis since the emphasis is on semester-long capstone team projects.

This course is an in-depth study of software development processes in the context of an actual project. Discussion includes object-oriented processes, such as Rational Unified Process, as well as process management issues such as scheduling, risk-assessment, various metrics, and the selection of appropriate development methodology and tools.

Introduction to computer communications networks. Topics include circuit-switching, packet switching, TCP/IP model layers, and wireless networks.

Design & implementation of operating systems. Topics include basic operating system structure, process and thread management, deadlocks, memory management, file management, input / output management, and distributed systems.

Introduction to computer security and privacy. Topics include security in programs, operating systems, networks and databases.

Topics in Computer Science

Introduction to Academic Research in Computer Science. Topics include: Research techniques and approaches, Computer Science research areas and metrics, literature review, writing a research paper, referencing and citations, and developing an effective workflow.

Practicum in Computer Science prepares students for successful computing related careers. The course aims to train and certify the students with market demanding fields such as computer networks, database systems, computer system/ applications, business and leadership etc.

Introduction to the design, development, and implementation of innovative solutions across various cutting-edge technologies. This course empowers students to tackle real-world problems by utilizing the latest technological tools and services. Students collaborate to create impactful projects, guided by both industry professionals and academic mentors, to address challenges in business and community settings.

Introduction to ethics theory and ethical decision making within the computing profession context. Topics include local and global impact of computing solutions, intellectual property, privacy, network security, electronic crimes and computer reliability.

This course is an examination of the concepts, theorems and problems which are fundamental to an understanding of economic decision making. Emphasis is on the real-life examples of fundamental concepts and application of quantitative methods to the solution of individual decision-making problems of households, firms and industries.

This is an introductory course in macroeconomics. The course is designed to introduce students to the essential concepts of macroeconomics. The approach is both analytical and policy oriented. Macroeconomics looks at the big picture of the economy. The course focuses on understanding the main macroeconomic problems, such as recession, inflation, and unemployment. In addition, the course analyses how fiscal and monetary policies can be used to influence macroeconomic performance and long-term growth.

Kuwait Economy will address the economic issues surrounding Kuwait. International trade, energy economics, cartels, optimal extraction rates, the Central Bank of Kuwait, and foreign investment issues are some of the topics that will be discussed. The class will draw on Kuwait’s rich history for examples and classroom discussions. Students are required to have taken introductory microeconomics and macroeconomics previously.

?This course is projected to help students understand the connections between money, financial markets, the banking sector and the macro-economy. How are interest rates determined and behave? How does the Federal Reserve (and central banks in general) conduct monetary policy? The course dedicates specific attention to the banking sector with an emphasis on their function, position, and importance in financial markets. Topics will include the role of the Federal Reserve as a lender of last resort during the recent, and previous, financial crises, unconventional monetary policy tools such as quantitative easing and forward guidance. We will often begin class with a discussion of current macro-financial market events in the context of our course coverage.

This course will provide an analytical framework for the understanding of the reasons for international trade in products and services. Students will learn to identify the determinants and patterns of international trade, and the effects on exchange rates of international capital flows in a free global market economy. The course will cover the role of international institutions in the development of international trade, financial markets, and economic growth. Students will be introduced to policies that distort international trade and prevent the development of comparative advantage, specialization and economic development.

This course is a survey of economic growth as applied to developed and developing countries. The course will include an analysis of development policies with emphasis on case studies.

International Energy Markets develops the basic economic foundations, technical and institutional knowledge necessary to formulate and implement sound economic, business and governmental policy decisions as they relate to international energy industries and institutions. This course will assist the student in understanding international energy markets, pricing, policies, and profits. Emphasis will be placed on understanding the energy markets from a producing country’s point of view.

We are living in an explosive era of readily available Big Data and statistics. Billions of users of cell phones, internet, GPS and medical devices generate 2.5 quintillion bytes of new data every day. The demand for analysts that can untangle and generate creative applications from this deluge of new data has never been higher across all walks of life. The course is designed to provide an understanding of fundamental concepts of data analysis and to use statistical and probabilistic thinking in the context of the modern business world. Particular emphasis will be placed on applying the theory to practical, real-world examples to enhance skills as an analyst, manager and observer of the world in general.

This course is an introduction to the applications of economics as a science and a profession. The course introduces students to the skills and tools that make economics an attractive and enjoyable field as an overview of economic data and current debates. The course builds on the knowledge that the student acquired in the principles classes and applies it to a variety of economic issues around the globe.

This course is an examination of the concepts, theorems and problems which are fundamental to an understanding of economic decision making. Emphasis is on the real-life examples of fundamental concepts and application of quantitative methods to the solution of individual decision making problems of households, firms and industries.

This course applies microeconomic analysis to specific business decisions. Managerial economics welds together microeconomic theory and the insights of management science in a decision-making format. This course concerns both theory and practice. Emphasis will be placed on demand analysis and estimation, production and cost analysis under different market conditions, and business and economic forecasting.

Natural Resource Economics considers the efficient and equitable use of society’s scarce natural resources. Natural resources include minerals, oil, fish, water and environmental systems. Natural resource use will be considered from three perspectives: the market allocation of natural resources, efficient and equitable allocations, and government attempts to achieve a more efficient and equitable allocation. The course will study in detail when the market is, and is not, capable of efficiently allocating natural resources.

The course will cover the following topics: construction of statistical models, especially the use of statistical tools and techniques such as chi-square tests of independence, analysis of variance, simple and multiple linear regressions and correlation, and the use of extrapolating methods such moving average and exponential smoothing.

Econometrics is concerned with how to use statistical methods and procedures for economic data. Econometrics techniques have been increasingly used in macroeconomics and applied microeconomics. It is concerned with estimating relationships, testing theories, and evaluating and forecasting impacts of business decisions. This course is designed to provide the students with sufficient knowledge of statistics and econometrics to be able to evaluate and interpret econometrics research that use basic linear regression methods. After completion of this course, students should be able to perform tasks of data collection, modeling of econometrics relationships, estimating and testing of the model, and interpreting and using the estimation results.