Global Arc

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You can now simultaneously browse international opportunities and on-campus courses; the goal is to plan coursework — before and/or after your trip — that will deepen your experiences abroad.

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Subject

Displaying 21 - 30 of 47
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Computer Science
Innovating Across Technology, Business, and Marketplaces
This course introduces computer science and technology-oriented students to issues tackled by Chief Technology Officers: the technical visionaries and managers innovating at the boundaries of technology and business. These individuals are partners to the business leaders of the organization, not merely implementers of business goals. The course covers companies from ideation and early-stage startup, to growth-stage startup, to mature company, covering the most relevant topics at each stage, including ideation, financing, product-market fit, go-to-market approaches, strategy, execution, and management. Exciting industry leaders guest lecture.
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Computer Science
Computational Geometry
Introduction to basic concepts of geometric computing, illustrating the importance of this new field for computer graphics, solid modelling, robotics, databases, pattern recognition, and statistical analysis. Algorithms for geometric problems. Fundamental techniques, for example, convex hulls, Voronoi diagrams, intersection problems, multidimensional searching. Two 90-minute lectures. Prerequisites: 226 and 240 or 341, or equivalent.
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Computer Science
Computer Networks
This course studies computer networks and the services built on top of them. Topics include packet-switch and multi-access networks, routing and flow control, congestion control and quality-of-service, Internet protocols (IP, TCP, BGP), the client-server model and RPC, elements of distributed systems (naming, security, caching) and the design of network services (multimedia, peer-to-peer networks, file and Web servers, content distribution networks). Two lectures, one preceptorial. Prerequisite: 217.
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Computer Science
Wireless Networks
This course covers the design and implementation of wireless networks, from signals to bits to datagrams. Students will gain an understanding of the principles and techniques behind the design of modern wireless local-area and wide-area networks, as well as their interaction with the design of the rest of the Internet. The class will provide an introduction to the wireless physical layer, presented in a way that is accessible for students with solely a computer systems and networking background.
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Computer Science
Web3: Blockchains, Cryptocurrencies, and Decentralization
This course serves as an introduction to the fast-developing world of Web3, focused on the applications of blockchains, cryptocurrencies, and decentralization through technology. Students will learn about blockchains and the decentralization of trust and power through technology, launch a cryptocurrency token, create non-fungible tokens, and build an application on a blockchain. We will also discuss applications, ethical implications, and policy questions around decentralization. See "Other Information" below.
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Computer Science
Pervasive Information Systems
The course covers devices and systems that provide information anywhere and any time. The underlying goals of pervasive information systems will be explored: business, entertainment, government, etc. Students will become familiar with all components of pervasive information systems such as lowpower electronics, audio/video, networking, and will consider human/computer interaction and geographically distributed systems.
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Computer Science
Natural Language Processing
Recent advances have ushered in exciting developments in natural language processing (NLP), resulting in systems that can translate text, answer questions and even hold spoken conversations with us. This course will introduce students to the basics of NLP, covering standard frameworks for dealing with natural language as well as algorithms and techniques to solve various NLP problems, including recent deep learning approaches. Topics covered include language modeling, rep. learning, text classification, sequence tagging, syntactic parsing, and machine translation. The course will have programming assignments, a mid-term and a final project.
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Computer Science
Neural Networks: Theory and Applications
Organization of synaptic connectivity as the basis of neural computation and learning. Multilayer perceptrons, convolutional networks, and recurrent networks. Backpropagation and Hebbian learning. Models of perception, language, memory, and neural development.
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Computer Science
Theory of Computation
Studies the limits of computation by identifying tasks that are either inherently impossible to compute, or impossible to compute within the resources available. Introduces students to computability and decidability, Godel's incompleteness theorem, computational complexity, NP-completeness, and other notions of intractability. This course also surveys the status of the P versus NP question. Additional topics may include: interactive proofs, hardness of computing approximate solutions, cryptography, and quantum computation. Two lectures, one precept. Prerequisite: 240 or 341, or instructor's permission.
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Computer Science
Introduction to Analytic Combinatorics
Analytic Combinatorics aims to enable precise quantitative predictions of the properties of large combinatorial structures. The theory has emerged over recent decades as essential both for the scientific analysis of algorithms in computer science and for the study of scientific models in many other disciplines. This course combines motivation for the study of the field with an introduction to underlying techniques, by covering as applications the analysis of numerous fundamental algorithms from computer science. The second half of the course introduces Analytic Combinatorics, starting from basic principles.