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Getting A Computer Science Degree 2
« on: January 29, 2016, 08:45:09 PM »
Computer science specializations

You can expect to begin your computer science degree by developing a foundation in key computer science topics. Some core computer science courses you may cover include theory of computation, fundamentals of computer science, compliers and operating systems, information theory, basic programming, systems and architecture, software development and testing, web applications and databases, algorithms and data structures, and principles of computer hardware. Mathematical concepts you may cover include formal methods, Boolean algebra, discreet mathematics, set theory, probability, statistics, linear algebra, differential equations and calculus.

You will then choose from an ever-growing range of specialist computer science topics, including advanced internet, advanced programming, artificial intelligence and artificial life, computational logic, computer graphics, computer modelling, computer networks, computer security, computer vision, encryption, ethical hacking, GUIs, games development, human-computer interaction, mobile applications, multimedia computing, networking theory, professional issues and research methods, software engineering and design, and web-development.

A closer look at some of the most popular computer science topics is provided below.

Programming language theory

Programming is an interdisciplinary topic, incorporating elements from subjects such as mathematics, software engineering and linguistics. Programming language theory involves looking at the design, implementation, analysis, characterization and classification of programming languages and their individual features. Your introductory courses will teach you one or more programming languages. Knowledge of more than one will help you to better understand their individual strengths and weaknesses, which will in turn help you to better engage with the challenges addressed by programming language theory. You’ll cover topics such as syntax, natural semantics, structural operational semantics and abstract machine code.

Computer graphics

Studying computer graphics involves using computers to create still or moving two or three dimensional images using specialized graphics hardware and software. You’ll study how to manipulate visual and geometric information using computational techniques, focusing on mathematical and computational foundations of image generation and processing rather than purely aesthetic issues. You’ll need knowledge of physics, light and materials, as well as knowledge of the mathematics of homogenous matrices, and of data storage, representation and manipulations. Computer graphics makes the interaction and understanding of computers and interpretation of data easier for both computing professionals and consumers. With companies exploring increased use of trends such as ‘gamification’, the demand for computer scientists with advanced knowledge of computer graphics has never been greater.

Human-computer interaction

The study of human-computer interaction (HCI) considers the challenges in making computers and computations useful, usable, and universally accessible to humans, in order to prevent unexpected problems caused by poorly designed human-machine interfaces. Coupled with studies rooted in behavioral sciences, you’ll cover the study, planning and design of this kind of interaction, with the understanding that a computer has an almost unlimited amount of uses which can only take place in an open-ended dialogue between the user and the computer. You’ll approach the subject on the machine side, with computing techniques such as computer graphics, operating systems, programming languages and development environments, and on the human side, exploring communication, graphics, linguistics, social sciences such as cognitive psychology, and user satisfaction.

Artificial intelligence

The study of artificial intelligence (AI) is closely related to the field of artificial life (AL), and both are involved in synthesizing goal-orientated processes such as problem-solving, decision-making, environmental adaptation, learning and communication using computers and algorithms. While the field of artificial life examines systems and studies the complex behaviors that emerge from these systems, artificial intelligence uses systems to develop specific behaviors in machines and software. AI is a cross-disciplinary topic drawing on applied mathematics, symbolic logic, semiotics, electrical engineering, philosophy (of mind), neurophysiology and social intelligence. AI involves the automation of tasks (such as evaluative and predictive tasks) in computer applications involving complex real-world data - successful use of AI in this manner can act as a viable substitute for humans doing the same tasks.

Algorithms and data structures

Algorithms are a step-by-step procedure for making calculations, used in data processing and automated reasoning - this creates an output that is often, but not always, predictable. Data structures provide a way of storing and organizing data in a computer so it can be used efficiently - different kinds of data structures are suited to different kinds of applications and may be highly specialized to specific tasks.

Together, algorithms and data structures underlie all other aspects of computer science, and involve learning how to store and process data as efficiently as possible, while ensuring algorithms are able to cope with the system in question. You’ll learn things such as linked lists, sorting and recursion, trees, hashing, greedy solutions, graphs and optimizing data arrangements. You may also go on to the analysis of algorithms (determining the amount of resources necessary to execute algorithms).
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Getting A Computer Science Degree

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