Ideas and techniques for designing, developing, and modifying large software systems. Another purpose of this presentation is for faculty to provide feedback on the quality of work to date. You'll work in a group to research and review selected protocols and techniques or design a solution to an advanced networking problem. Group study of selected topics in electrical engineering, usually relating to new developments. Preferred: experience developing software at level of COMPSCI61B and experience using Linux. Introduction to the theory and practice of formal methods for the design and analysis of systems, with a focus on algorithmic techniques. Computer Science 109: Introduction to Programming consists of short video lessons that are organized into topical chapters. Demonstrate how to communicate clearly and effectively in a range of situations. Fundamental bounds of Shannon theory and their application. That's why we are committed to offering a scholarship that makes it easier for gifted, ambitious international learners to pursue their academic interests at one of the UK's most prestigious universities. Enter the College of Letters & Science (L&S) and, after successful completion of the courses required to declare with the minimum grade point average (GPA), petition to be admitted to the L&S Computer Science major. Stability analysis. This programme of study should reflect a solution to a problem of the student's devising. Program analysis, optimization, and transformation; partial evaluation; object-oriented programming; transformation of formal specifications; specialization of generic procedures; views. Power conversion circuits and techniques. Hence the pre-requisite for this course is that a student has taken the CS150 course in the Fall 2014. Laboratory in the Mechanics of Organisms: Read More [+], Prerequisites: INTEGBI135 or consent of instructor. Recent placement students have worked at large organisations such as Apple, BT, IBM, Intel, GSK, Microsoft, and Xerox. Simulation based laboratory and design project. Data Structures and Programming Methodology: Great Ideas of Computer Architecture (Machine Structures). Emphasis on design, not fabrication. Naming. Originally studying atHertswasn't my primary choice, although when I opened myUCASapplication and saw my results I was overwhelmed with excitement and I immediately discussed with my family that I wanted to confirm my place at the university, my family were supportive and my dad even drove us to theuniand we explored the campus and spoke with current students about their experience, after hearing and seeing awelcomingand warm atmosphere I wanted to confirm my place on my UCAS application. You'll explore virtual reality (VR), 3D web authoring, 3D printing and prototyping, 3D visualisation and simulation, and creation of movies and video games. These seminars are offered in all campus departments; topics vary from department to department and from semester to semester. Prerequisite: Graduate standing and knowledge of algorithms, probability, and linear algebra. You can build your personalised network of support from the following people and services: Your personal tutor helps you make the transition to independent study and gives you academic and personal support throughout your time at university. Susan L. Graham, Professor Emeritus. Student Learning Outcomes: Students will learn how to apply BDD & TDD to identify the main parts of a legacy code base, measure code quality, and refactor code to improve its quality; The techniques you'll learn about include feature detection, segmentation, motion tracking and shape recognition. Study.com has been awesome to work with! Feedback linearization and sliding mode control methods. Computer Architecture & Engineering (ARC), Operating Systems & Networking (OSNT), Computer System Performance Analysis, I/O Systems, Cache Memories, Memory Systems. Transfer credit may be awarded for a maximum of four semester or six quarter units of graduate coursework from another institution. This may be fulfilled by completing one of the following courses: BIOENG100*, COMPSCI195,COMPSCIH195, ENE,RESC100*, ENGIN125*, ENGIN157AC*, IAS157AC*, ISF100D*. Relation to human visual perception. Practical exercises to model and develop and embedded systems will strengthen the understanding of the taught concepts. Students planning to use Plan I for their MS Degree will need to follow the Graduate Division's Thesis Filing Guidelines." Optoelectronics Research Group, high speed optical communications, photonic crystals at optical and microwave frequencies, the milli-Volt switch, optical antennas and solar cells , Physical Electronics (PHY).Research Profile, Katherine A. Yelick, Professor. Visit the Berkeley Graduate Divisionapplication page. Adaptive Instruction Methods in Computer Science. Covering popular subjects like HTML, CSS, JavaScript, Python, SQL, Java, and many, many more. - Definition & Examples, What is a Class in Java? It must be given before the final submission of the dissertation. Students will learn program design, control structures, data types, arrays, algorithms, documentation, testing, debugging; and principles of object-oriented design, including encapsulation, polymorphism, and abstraction. Prerequisite: Graduate standing; and Computer Science 388G, or consent of instructor. Nonlinear phenomena, planar systems, bifurcations, center manifolds, existence and uniqueness theorems. Programming shared- and distributed-memory parallel computers, GPUs, and cloud platforms. Application of techniques and strategies of effective technical writing, and of conventions used in documents such as letters, memos, proposals, abstracts, and reports. Computer Science 439 and 439H may not both be counted. Array and matrix operations, functions and function handles, control flow, plotting and image manipulation, cell arrays and structures, and the Symbolic Mathematics toolbox. Our goal is to prepare students both for a possible research career and long-term technical leadership in industry. Sequential execution: partial and total correctness; deductive, operational, and denotational semantics; formal derivation of programs; parallel execution: partial correctness, deadlock, and starvation; methodology, parallel versus distributed execution. Kannan Ramchandran, Professor. Applying for part-time or distance learning courses, Portsmouth Football Club Partnership Scholarship, 3000 Master's scholarship for current students, 3000 Master's scholarship for new students, How we assess your postgraduate application, After you apply for a postgraduate course, Writing a research proposal and personal statement, Accounting, economics and finance courses, Business, management and marketing courses, Childhood, youth studies and education courses, Computer games, animation and digital technologies courses, Data science and machine learning courses, Fashion, photography, graphic arts and design courses, Geography and environmental science courses, History, politics and international relations courses, Criminal Justice part time distance learning courses, Faculty of Creative and Cultural Industries, Faculty of Humanities and Social Sciences, Criminal Justice Studies Short Courses and CPD, Inbound students: choose what youll study, researching artificial intelligence that could save lives, winning awards for prototype software to predict a Covid-19 diagnosis, see full entry requirements and other qualifications we accept, accept other standard English tests and qualifications, how our teaching has transformed to best support your learning, support via video, phone and face-to-face, funding options for international students, BSc (Hons) Cyber Security and Forensic Computing, BEng (Hons) Engineering and Technology with Foundation Year, Specialise in areas such as artificial intelligence (AI), cybersecurity, robotics, data mining, cryptography and the Internet of Things (IoT), Take part in fast-paced hackathons and visit companies with specialist computer science departments, UCAS points 112128 points, including an A Level in a relevant subject, or equivalent (. Senior Honors Thesis Research: Read More [+]. Study computer systems and internetworking (connecting various types of networks to create one large network) and consider how they support digital technologies. Prerequisite: Computer Science 313E, 314, or 314H with a grade of at least C-. Solid-State Devices, Nano-Optoelectronics, Electromagnetics/Plasmas. We use cookies to give you the best online experience. Professional Preparation: Supervised Teaching of Computer Science: Terms offered: Fall 2015, Fall 2014, Spring 2014, Terms offered: Fall 2017, Fall 2016, Fall 2015, Terms offered: Spring 2011, Spring 2010, Fall 2006, Terms offered: Spring 2022, Spring 2021, Fall 2019. Prerequisite: Graduate standing. Examine the latest in virtualization technologies such as virtual machines, containers and serverless computing. Model-driven engineering; UML metamodels and constraints, model transformations, software product lines, feature models, feature modularity, feature algebras, feature interactions, multi-dimensional separation of concerns, design-by-transformation, parallel software architectures, correct-by-construction, architecture refinement, optimization, and extension, program refactorings, design patterns, refactoring scripts, category theory, functors, commuting diagrams. Prerequisite: Computer Science 313E, 314, or 314H with a grade of at least C-. Subjects include proof by induction, introduction to graph theory, recurrences, sets, functions, and an introduction to program correctness. Programming projects are required. These sections are designed to enhance any interns, tutors, or TAs teaching skillset. If you combine this module with language study in your first or third year, you can turn this module into a certificated course that isaligned with the Common European Framework for Languages (CEFRL). In the object-oriented programming paradigm, object can be a combination of variables, functions, and data structures; in particular in class-based variations of the paradigm it refers to a particular instance of a class. Student Learning Outcomes: Students will learn how to approach and add functionality to a legacy code base; Students must demonstrate command of the content and the ability to design and produce an acceptable dissertation. The equivalent of three lecture hours a week for one semester. Develop technology that will define the future. Three lecture hours a week for one semester. The labs exercises culminate with a large design project, e.g., an implementation of a full 3-stage RISC-V processor system, with caches, graphics acceleration, and external peripheral components. Programming Systems (PS), Scientific Computing (SCI), Biosystems & Computational Biology (BIO), parallel programming techniques.Research Profile, Nir Yosef, Assistant Professor. Numerical Simulation and Modeling: Read More [+], Prerequisites: Consent of instructor; a course in linear algebra and on circuits is very useful, Fall and/or spring: 15 weeks - 4 hours of lecture per week, Numerical Simulation and Modeling: Read Less [-], Terms offered: Spring 2016, Spring 2015, Spring 2011 manipulation of non-rigid objects. Elements of Materials Science (4) The structure of materials: metals, ceramics, glasses, semiconductors, superconductors, and polymers to produce desired, useful properties. Our Chaplaincy is home to Chaplains from the Christian, Jewish and Muslim faiths. Topics include design flows, discrete and continuous models and algorithms, and strategies for implementing algorithms efficiently and correctly in software. Graduation is only a few years away and it's not too early to find out. Modeling and control of aggregated storage devices, power management, and system analysis of energy technologies and their impact.Research Profile, John Canny, Professor. Formerly known as: Electrical Engineering 127, Optimization Models in Engineering: Read Less [-], Terms offered: Fall 2022, Fall 2021, Fall 2020 Quantum information processing is an active research area that exploits fundamental quantum phenomena in new applications from computation, secure data communication and information processing. Hierarchical, network, relational, and object-oriented data models. Three lecture hours a week for one semester. Principles of Magnetic Resonance Imaging: Applications of Stochastic Process Theory, Terms offered: Spring 2017, Spring 2013, Spring 1997. Special attention will be devoted to the most important challenges facing digital circuit designers in the coming decade. This module covers the issues and terminology in communicating sequential processes. Topics include: language modeling, speech recognition, linguistic analysis (syntactic parsing, semantic analysis, reference resolution, discourse modeling), machine translation, information extraction, question answering, and computational linguistics techniques. The student must repeat the course each work period and must take it twice to receive credit toward the degree; at least one of these registrations must be during a long-session semester. Advanced Topics in Computer Systems: Read More [+], Prerequisites: COMPSCI162 and entrance exam, Advanced Topics in Computer Systems: Read Less [-], Terms offered: Spring 2020, Spring 2009, Fall 2008 This module has been devised for direct entrants to the final year of our computing degrees. Combinatorics and Discrete Probability: Read More [+], Instructors: Bartlett, Papadimitriou, Sinclair, Vazirani, Combinatorics and Discrete Probability: Read Less [-], Terms offered: Fall 2020, Fall 2018, Fall 2017 Prerequisite: Graduate standing; Computer Science 367 or Mathematics 368K; and Mathematics 340L, 341, or consent of instructor. Hafsa's time as a student at the University helped ready her for employment in many ways. Employ best practice methods and approaches to manage a large-scale project, Identify and summarise the problem to be solved and put it in context, Identify legal, ethical, social and professional issues relevant to your project and take necessary action(s) to address these issues, Conduct a formal literature search, identifying, analysing, comparing and contrasting sources and writing an evaluative review, Design, implement and test a substantial relevant artefact (or several smaller artefacts), Critically evaluate your work against its objectives, reflecting and generalising on the learning achieved in your written report, a 10,000-word report (100% of final mark), Demonstrate practical skills in the design of automata, Solve and analyse computation complexity of algorithms for practical problems, 12 x 2 hours of practical classes & workshops, a 90-minute set exercise exam (50% of final mark), Evaluate the needs and requirements for wireless network technologies, Identify the limits and applications of current networks and examine alternative technologies, Apply the principles of security, error controls, modulations, and impairments of communication principles to the network technology, Evaluate, assess and simulate the different techniques that shape the emergence of new network technologies, Analyse, simulate and evaluate current network configurations and technologies, identify issues and provide solutions, a 1.5-hour written exam (60% of final mark), Build effective lessons with clear learning objectives that take into account specific needs of learners and conform to your placement schools ethos and policies, Provide evidence of progress and achievement against the current Teachers Standards, Demonstrate development of subject knowledge and understanding of methods and practices of teaching Computer Science, Demonstrate an understanding of contributory factors that make up a successful school, 27 hours of practical classes & workshops, a 3,000-word set exercise (30% of final mark), Apply theories of learning and cognition to the evaluation of learning materials for delivery on computers, Select and link an appropriate set of resources for a given scenario related to educational computing and technology, Evaluate the concept of a 'Personal Learning Environment' (PLE) and start to develop one, Research current trends in software, hardware and applications, and how this can relate to the use of IT in learning, 24 hours of practical classes and workshops, a 1,200-word set coursework exercise (40% of final mark), a 2,800-word set coursework exercise (60% of final mark), Recognise the issues and technological trends that influence the design of a web application, Explain the critical features of advanced techniques for web application development, Appraise web technologies for use in an application and choose an appropriate architecture for your project, Design and implement a web application and web services, Integrate web applications with multiple data sources, a programming project (50% of final mark), Use and reflect on the mathematical foundations of fuzzy logic, Choose and apply techniques for building fuzzy systems and networks, Analyse and design fuzzy systems and networks with specialised software, Appraise the principles and methods of 3D computer graphics and their current implementations, Analyse and solve computer vision problems using essential computer vision methods, Apply 3D graphics methods, web programming languages and APIs to real world problems, Use and evaluate appropriate computer vision methods and tools, Show a sophisticated and empirically-grounded understanding of pressing security challenges facing the UK government, Engage critically with a range of methodological tools and approaches commonly used to address security-related challenges, Demonstrate a deep understanding of the practical dynamics underpinning team-based approaches to addressing security-related challenges and solutions, Develop critical analysis, independent judgment, complex problem solving, team coordination and an oral and written presentation to degree level, a 4,000-word coursework report (100% of final mark), Evaluate the design and development of technologies on different layers, for typical IoT systems, Evaluate the current and emerging issues in the research and development of IoT that cover current architectures, technologies, applications and trends, Develop effective applications or protocols to exploit commercially available sensors and actuators in an IoT architecture, a 1,500-word portfolio (50% of final mark), Appraise nature inspired computational intelligence models, such as Genetic Algorithms (GA) and Artificial Neural Networks (NN), and discuss their theoretical foundations, Design, train, critically evaluate and implement a variety of NN architectures and GA algorithms for solving practical problems, 12 x 1-hour practical classes and workshops, a 90-minute written exam (60% of final mark), Analyse the performance of different data mining techniques, Select and apply appropriate data mining techniques for analysis tasks, Describe how data mining design and implementation methods could be used to solve problems, 24 x 2-hour practical classes & workshops, Critically evaluate and synthesise theoretical, contextual and practical issues relating to a range of research skills, Analyse professional and ethical issues within the ICT discipline, Reflect on and critically evaluate the extent to which the existing BCS/IEEE professional codes of practice and ethics might apply in actual workplace situations, Evaluate opportunities for IT in computing, a 4,000-word coursework portfolio (100% of final mark), Appraise the principles and methods of robot sensing and motion control, Analyse different approaches and techniques in the robot sensing and control algorithms and systems, Apply computational intelligent algorithms to real robotic systems, Implement and develop practical programming skills for robot decision-making, robot motion control and human-robot interaction and collaboration in modern robotic systems, Analyse a cryptographic system, identify vectors for attack, and determine mechanisms for closing vulnerabilities, 12 x 2-hour practical classes and workshops, a 1-hour written exam (40% of final mark), Demonstrate a comprehensive understanding of current advanced methods and techniques in data and text analytics, Design and implement data mining based applications to solve real-world problems, Critically analyse and evaluate the performance of different data mining techniques for text analysis, and analyse and interpret the data mining results, Appraise the principles and methods of image processing and computer vision, Analyse different approaches and techniques in the design of computer vision algorithms/systems, Apply computer vision algorithms to real world problems, Implement and develop practical software skills for computer vision applications, Work effectively both as an individual and as part of a team developing software for an external client, Assess and develop existing knowledge from a range of areas and apply it to solving a problem, Plan and manage a significant project to meet stated technical and business objectives, Critically appraise and reflect upon the management, delivery and outcome of a project, 2 hours of practical classes and workshops, Evaluate the applicability of current parallel processor architectures and their associated programming environments to significant classes of computational tasks, Analyse computational problems to expose exploitable parallelism, and estimate or measure the performance improvements that can be achieved through this parallelism, Develop effective parallel programs to exploit commercially important parallel architectures, Explain at an appropriate level mathematical methods of scientific computation, Implement algorithms to simulate and visualize selected physical and biological systems and analyse scientific data, Adapt scientific algorithms to exploit high performance and parallel computation platforms, Assess and evaluate existing software platforms for kinds of scientific computing discussed in the module, master the mathematics skills you need to excel on your course, understand engineering principles and how to apply them in any engineering discipline, solve computing problems relevant to your course, develop your knowledge of computer programming concepts and methods relevant to your course, discuss and agree on reasonable adjustments, liaise with other University services and facilities, such as the library, access specialist study skills and strategies tutors, and assistive technology tutors, on a 1-to-1 basis or in groups, UK/Channel Islands and Isle of Man students 925 a year (may be subject to annual increase), EU students 925 a year, including Transition Scholarship (may be subject to annual increase), International students 1,800 a year (subject to annual increase), the UCAS course code G400 (BSc) orI100 (BEng), Tour our campus, facilities and halls of residence, Speak with lecturers and chat with our students, Get information about where to live, how to fund your studies and which clubs and societies to join. And the best thing about it is, youdon'thave to be an elite athlete to take part. Student Learning Outcomes: Although the syllabus is the same as EECS151LB, the assignments and exams for EECS251LB will have harder problems in labs and in the project that test deeper understanding expected from a graduate level course. Techniques for synchronization and load balancing. Explore an advanced overview of autonomous mobile robotics, including control, perception, and planning. Fundamental concepts of structured programming; procedures and data structures with a focus on problem solving strategies and implementation; introduction to concepts of informal specification, informal reasoning about program behavior, debugging, and ad hoc testing.
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