It covers the key algorithms for robot intelligence through inference, planning, and learning, and also provides some practical experiences with modern robot systems. Programme Structure for Bachelor of Engineering (Computer Engineering) Please refer to https://ceg.nus.edu.sg/ for details. CS3103L Computer Networks Laboratory (defunct). The module emphasizes on the understanding of the principles of neural networks and deep learning; practical guidelines and techniques for deep learning; and their applications. It covers a range of topics including network performance (throughput, delay, Little’s Law and M/M/1 queuing formula), and resource allocation and buffer management (max-min fair, round-robin and RED), intra- and inter-domain routing (RIP, OSPF and BGP), congestion control and modern variations of TCP (AIMD and Cubic TCP), peer-to-peer applications and content delivery networks (BitTorrent, Skype, Akamai), and data center networking and management (SDN and OpenFlow). Selected topics may include: secret sharing, TCP/IP security, Kerberos, SSL, trusted computing, side-channel attacks. Topics covered include, but are not restricted to, linear programming, graph matching and network flows, approximation algorithms, randomised algorithms, online algorithms, local search algorithms, algorithms for large datasets. The module will provide students with insights into the innovation process and case studies of successful innovation. This module reveals all the exciting behind-the-scene techniques that make these movies and games possible, including but not limited to motion capture, fluid animation, facial animation, and full-body character animation. CS1102 Data Structures and Algorithms (defunct). To extract water from this under utilised source, a team led by Professor Ho Ghim Wei from the NUS Department of Electrical and Computer Engineering created a type of aerogel, a … CS2113T Software Engineering & Object-Oriented Programming. Topics include the design principle of instruction set, memory hierarchy, pipeline design techniques, RISC and vector computer. Topics include: C programming: Variables, types, operators, expressions, control flow, functions, function arguments, recursion, pointers, address arithmetic, arrays, structures, standard input/output. Otherwise, CS2113 and CS2113T are identical. Modular credits: 4 Workload: 2-0-0-5-3 Prerequisite(s): CS5234 Preclusion(s): Nil Cross-listing(s): Nil This module is aimed at graduate students who are doing or intend to do advanced research in algorithms design and analysis in all areas of computer science. Starting from a small core of fundamental abstractions, the module introduces programming as a method for communicating computational processes. Students will be exposed to the workings of common media file format and common manipulation techniques on media data. CS4231Parallel and Distributed Algorithms 4. This has ushered in a new era of communications that involves complex information exchanges and user relationships. CS3215 Software Engineering Project (defunct). Apart from a variety of programming assignments, this course will also introduce students to some relevant research topics in this area. Upon completion, the students should be able to understand the foundations of multimedia computing, and apply computational tools to the processing of multimedia data in order to create specific applications. It introduces the language processing techniques of interpretation and compilation. Our focus will be on system-level design techniques, with the aim of critically accessing known models and methods in terms of their generality and ability at different stages of an embedded system design process. The main topics covered are greedy algorithms, layering, polynomial time approximation schemes, (randomised) rounding and LP-relaxation. This aim of this module is to cover algorithms related to this stage. * CEG student's faculties refer to both Faculty of Engineering and School of Computing. This module focuses on understanding and controlling the sources of latency in a datacentre, especially the long-tail delays that ruin a user experience. CS1102C Data Structures and Algorithms (defunct). Students will round out their knowledge with case studies of how different disciplines (e.g. This module introduces the students to basic theories, concept and practical skills needed in input, processing and output of multimodal data on mobile platforms. They will also gain an appreciation of how choosing the wrong technologies and tools can be disastrous to the project, and the pitfalls and opportunities for automation of software development. Topics covered include network data in social and digital media, formal methods for social network analysis, analytics and visualization tools, population and structural models for network dynamics, and various industry case studies on social and digital media analytics. CS5237 Computational Geometry and Applications. Modular Credits: 4 Workload: 2-1-0-3-4 Prerequisite(s): (CS1020 or CS1020E or CS2020) or ((CS2030 and (CS2040 or CS2040C)) Preclusion(s): CS2103T, CS2113, CS2113T. This module familiarizes students to security issues in different stages of the software life-cycle. Modular Credits: 4 Workload: 2-1-0-3-4 Prerequisite(s): CS3223 Preclusion(s): CS4225 Cross-listing(s): Nil This module studies the management of data in a distributed environment. (EC) students. Modular Credits: 4 Workload: 2-1-0-3-4 Prerequisite(s): CS2100 or CG2007 or EE2024 Preclusion(s): Nil Cross-listing(s): Nil The aim of this module is to provide an introduction to the field of parallel computing with hands-on parallel programming experience on real parallel machines. The course also describes and compares various advanced programming language features. In the context of this exciting development, the aim of this module is to examine the design issues that are critical to modern parallel architectures. Well-Ordering Principle. They will also engage in hands-on practice of digital video production. The emphasis is on the formulation and techniques of various cryptographic primitives, and on the secure usage of such primitives to achieve the goals of confidentially, integrity, and authenticity in both theoretical settings and practical scenarios. It covers techniques for attacking and solving challenging computational problems. You can choose from a diverse range of modules, spanning areas like computer systems, data management, programming language, software engineering, artificial intelligence (Al), human-computer interaction (HCI), and algorithms. It also trains students to work well in project teams. In addition, students are exposed to various algorithm design paradigms. Topics covered include trees, binary search trees, order property, prefix/infix/postfix expressions, heaps, priority queues, graphs and their algorithmic design, recursive algorithms, problem formulation and problem solving with applications of complex data structures, data structure design principles and implementation strategies, and algorithm analysis. The syllabus optionally includes selected topics in the technologies, design and performance tuning of non-relational database applications (for instance, network and hierarchical models and nested relational model for an historical perspective, as well as XML and NoSQL systems for a modern perspective). It examines issues, challenges, and techniques in problem representation, goal or objective specification, response selection, and action consequence for a wide range of strategic and tactical planning and decision making situations. These concepts will be tied together through hands-on practice in building a Web-based application using the current Web development technology. The module covers design decision exploration as well as patterns that explicate principles and best practices in replicable form. 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