This course is an integrative experience that brings together all components of the undergraduate information technology curriculum in an applied, hands-on real world setting. This course focuses on project development, including background study, functional design, plan schedule, interface and algorithm implementation. Lectures are given for assisting the students in project development with necessary background and technical topics. Most lecture hours will be allocated for group discussion, procedural reports, group or individual questions as well as documentation and programming.
In this course, the students will become familiar with the different phases of information systems development. Discussion will concentrate on the initiation, analysis, design, development, implementation and maintenance of a system and the different tools used in system analysis and design. This course strikes a balance between the theoretical and applied aspects of systems analysis, presenting state-of-the-art systems, procedures, methodology and software. These skills are applied by allowing students to experience analyzing and designing a "live" system for a target client.
This course studies the process of integrating different systems and software application by examining current and emerging trends, strategies, and techniques for developing systems integration solutions effectively. Example topics covered include, but are not limited to: documenting integration requirements using business process models, designing integration solutions reusing patterns, and implementing integration solutions using service oriented architecture. Students will extend course topics via library assignments, programming assignments, tool evaluation assignments, and other assigned activities.
This course aims to help the student to develop their analytical and problem-solving skills, particularly concerning thinking algorithmically.
This covers fundamental concepts of data structures and algorithms starting with linear data structures such as Arrays, Lists, Queues & Stacks then looking at associative data structures such as trees and graphs. The study of these data structures will cover their capabilities, performance characteristics, and applications.