University of texas at arlington background for computer

  1. University of Texas, Arlington
  2. India Study Abroad - Kunal Parashar
  3. Center for Distance Education
  4. Professors from UT-Arlington, UT-Dallas join forces to fight fake news
  5. The University of Texas at Arlington Student Population Stats

Prerequisites: Departmental good standing and permission of instructor. May be taken a maximum of 3 times.

Introduction to basic engineering concepts. Students will become familiar with engineering and its many sub-fields, ethical responsibilities, creativity and design.

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Introduction to engineering concepts, the computer science and engineering disciplines, skills for written communication, and departmental orientation. For those persons having an interest in finding out what a computer is and is not , the types of problems suited for computers, and how to utilize a computer to solve problems. The organization and characteristics of computers; application of commercial software such as word processors, spreadsheets, database packages, and communications packages. An introduction to the algorithmic process and to programming using basic control and data structures.

This course is taught using the Python programming language. An introduction to the computer, to the algorithmic process, and to programming using basic control and data structures, using a procedural language. An introduction to the computer, to the algorithmic process, and to programming using basic control and data structures.

This class is currently using the C language. Programming concepts beyond basic control and data structures. Emphasis is given to data structures including linked-lists and trees as well as modular design consistent with software engineering principles. Object-oriented concepts, class diagrams, collection classes, generics, polymorphism, and reusability.

Projects involve extensive programming and include graphical user interfaces and multithreading. New developments in the field of computer science and engineering.

Topic may vary from semester to semester. May be repeated for credit when topic changes. Departmental approval required in advance to use for degree credit. Prerequisite: consent of advisor. Sophomore level undergraduate research course. A practical approach to hands-on computer hardware and software systems in a laboratory environment. Students will be exposed to basic design concepts using off-the-shelf hardware components and to tools that enable the design of complex software systems. Computer organization from the viewpoint of software, including: the memory hierarchy, instruction set architectures, memory addressing, input-output, integer and floating-point representation and arithmetic.

The relationship of higher-level programming languages to the operating system and to instruction set architecture are explored.

University of Texas, Arlington

Some programming in an assembly language. Propositional and predicate logic, mathematical proof techniques, sets, combinatorics, functions and relations, graphs, and graph algorithms. Design and analysis of algorithms with an emphasis on data structures.

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Approaches to analyzing lower bounds on problems and upper bounds on algorithms. Classical algorithm design techniques including algorithms for sorting, searching, and other operations on data structures such as hash tables, trees, graphs, strings, and advanced data structures, dynamic programming and greedy approaches.

Basic principles of electrical circuits using resistors, capacitors and inductors. Filter analysis and synthesis using complex algebra. Introduction to operational amplifiers. Time domain and frequency domain analysis and taxonomy of signals. Concurrent laboratory experiments complement lecture topics. Analysis, design and testing of combinational and sequential logic circuits.

Computer aided design tools and utilized throughout the course.

India Study Abroad - Kunal Parashar

Junior level undergraduate research course. Introduction, analysis, and evaluation of the important concepts found in a variety of programming languages. Formalisms useful in specifying language syntax and semantics; programming language paradigms such as algorithmic, functional, logic, and object-oriented. Software engineering principles, processes, and techniques; software development approaches focusing on functional analysis and functional design methods.

Configuration management, implementation strategies, and testing. Team project. Study of an agile unified methodology and its application to object-oriented software development. Topics include requirements acquisition, use case derivation, modeling and design of interaction behavior and state behavior, introduction to design patterns, derivation of design class diagrams, implementation considerations and deployment.

Examines models for presentation and processing of digital signals. Sampling theorem, correlation and convolution, time and frequency analysis of linear systems, Fourier transform, Z-transform, design of digital filters structures for discrete time systems.

Center for Distance Education

Selected theoretical concepts including regular and context free languages, finite state and pushdown automata, Turing machines, computability, and NP-completeness. Functions and components of an operating system, including process synchronization, job scheduling, memory management, file systems protection, and deadlocks. Related system software, such as loaders, linkers, assemblers, and windowing systems. Solving systems of equations, matrix algebra, determinants, vector spaces, orthogonality and least squares, with applications to computer science.

Senior level undergraduate research course. Special problems in computer science and engineering on an individual basis.

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Topics may change from semester to semester. May be repeated for credit. Departmental approval must be obtained in advance for degree credit. Prerequisite: consent of instructor and department chairperson. Theory and practice for the visual representation of data by computers including display devices, output primitives, planes and curved surfaces, two- and three-dimensional transformations, parallel and perspective viewing, removal of hidden lines and surfaces, illumination models, ray tracing, radiosity, color models, and computer animation.

Prerequisite: Admitted into an Engineering Professional Program.

Review of programming language structures, translation, and storage allocation. Theory and practice of compilers and issues in compiler construction including parsing, intermediate code generation, local optimization problems such as register allocation, data-flow analysis, and global optimization. An introduction to the field of artificial intelligence studying basic techniques such as heuristic search, deduction, learning, problem solving, knowledge representation, uncertainty reasoning and symbolic programming languages such as LISP.

Application areas may include intelligent agents, data mining, natural language, machine vision, planning and expert systems. This course offers an introduction to machine learning. Topics include naive Bayes classifiers, linear regression, linear classificiers, neural networks and backpropagation, kernel methods, decision trees, feature selection, clustering, and reinforcement learning.

The University of Texas at Arlington Student Population Stats

A strong programming background is assumed, as well as familiarity with linear algebra vector and matrix operations , and knowledge of basic probability theory and statistics. This course introduces students to basic concepts and techniques in computer vision. The topics covered include morphological operations, connected component analysis, image filters, edge detection, feature extraction, object detection, object recognition, tracking, gesture recognition, image formation and camera models, calibration, and stereo vision.

Contemporary social aspects and responsibilities of computing in a global, societal context. Lifelong learning goals and resources. Entrepreneurship and intellectual property. Project involving written and oral communication. Analysis and design of an industry-type project that involves hardware and software components to meet desired needs within realistic constraints and standards. Techniques for system modeling and simulation of stochastic and knowledge-based systems. Modeling methods, model validation and verification procedures, and steady state solution techniques.