Recommended that CS Majors have also taken one of 142, 193P, or 193A. In doing so, we'll see a number of classic data structures like Fibonacci heaps and suffix trees as well as more modern data structures like count-min sketches and range minimum queries. 1 Unit. Limited enrollment, permission of instructor required. Advanced Systems Laboratory, Accelerated. You Say You Want a Revolution. CS 448. Topics: varieties of parallelism in current hardware (e.g., fast networks, multicore, accelerators such as GPUs, vector instruction sets), importance of locality, implicit vs. explicit parallelism, shared vs. non-shared memory, synchronization mechanisms (locking, atomicity, transactions, barriers), and parallel programming models (threads, data parallel/streaming, MapReduce, Apache Spark, SPMD, message passing, SIMT, transactions, and nested parallelism). In a playback show, a group of actors and musicians create an improvised performance based on the audience's personal stories. Students register under their faculty advisor during the quarter they are employed and complete a research report outlining their work activity, problems investigated, results, and follow-on projects they expect to perform. This class will culminate in an open-ended final project, which the teaching team will help you on. Studio based format with intensive coaching and iteration to prepare students for tackling real world design problems. CS 428. For advanced undergraduates and for graduate students. CS 448I. Focus is on Macintosh and Windows operating system maintenance, and troubleshooting through hardware and software foundation and concepts. Significant amount of additional advanced material and substantially more challenging projects. How will society respond as versatile robots and machine-learning systems displace an ever-expanding spectrum of blue- and white-collar workers? Prerequisite: CS 106B; recommended: CS161; consent of instructor for 3 units. Hardware Accelerators for Machine Learning. Business and Professions Code section 3502.1(e)(3) states a PA who holds an active license, who is authorized through a practice agreement to furnish Schedule II controlled substance, who is registered with the U.S. Drug Enforcement Administration, and who has not successfully completed a one-time course … 3 Units. Basic knowledge of probability, linear algebra, and calculus. 3-4 Units. Recursion and recursive data structures (linked lists, trees, graphs). 3-5 Units. Substantial, quarter-long course project that will be presented in a public presentation. Recommended: basic Unix. It also provides an overview of different robot system architectures. All students will learn to work together across disciplinary divides to solve technical, legal, and practical problems. CS 148: Introduction to Computer Graphics and Imaging. The class meets once a week for the first 6 weeks of the quarter. Prerequisites: CS161 and CS154. Topics include tail bounds, the probabilistic method, Markov chains, and martingales, with applications to analyzing random graphs, metric embeddings, random walks, and a host of powerful and elegant randomized algorithms. Metric Embeddings and Algorithmic Applications. May be repeated for credit. Prerequisite: CS107. Applications range from the design of aircraft to automated vehicles. Prerequisites: knowledge of linear algebra, discrete probability and algorithms. Motivated by graphics concepts, mathematical foundations and computer algorithms, students will explore an eccentric selection of "great ideas" through short weekly programming projects. As black-box AI models grow increasingly relevant in human-centric applications, explainability and fairness becomes increasingly necessary for trust in adopting AI models. Topics in Programming Language Theory. Emphasis is on the general principles of image processing. The course can be thought of as an applied formal methods course where the application is reliable and secure architecture, microarchitecture, and distributed systems design. 3 Units. Prerequisite: CS255. Students will work with computational and mathematical models and should have a basic knowledge of probabilities and calculus. CS 103. Seminar goal is to expose students from engineering, medicine, and business to guest lecturers from academia and industry. Join us as we go behind the scenes of some of the big headlines about trouble in Silicon Valley. Continuation of CS210A. Same as: ME 571. 3 Units. This project-based course will provide a comprehensive overview of key requirements in the design and full-stack implementation of a digital health research application. If you¿re quick to action, this course will give you a wider foundation for making a positive impact. Topics include programming and problem solving; implementing computation in hardware; algorithmic efficiency; the theoretical limits of computation; cryptography and security; computer networks; machine learning; and the philosophy behind artificial intelligence. Taught by a team of law and engineering faculty, this unique interdisciplinary course will empower students across the University to work together and exercise leadership on critically important debates at the intersection of law and digital technology. Students lead a discussion section of 106A while learning how to teach a programming language at the introductory level. 3 Units. In this seminar, we will explore these questions through the lenses of philosophy and computation. 3-4 Units. Topics in Computer Graphics. You will practice all these ideas in Python and in TensorFlow, which we will teach. Same as: INTLPOL 251. Class covers relevant results from geometry, kinematics, statics, dynamics, motion planning, and control, providing the basic methodologies and tools in robotics research and applications. Students will also gain experience with key technologies for the creation of autonomous robots, including perception, action, human-robot interaction, and learning. Computer Science and Engineering (CSE) Computer Science (COMPSCI) Criminology, Law and Society (CRM/LAW) Criticism (CRITISM) Culture and Theory (CLT&THY) D. Dance (DANCE) Developmental … 2 Units. Course projects include writing security exploits, defending insecure web apps, and implementing emerging web standards. The course culminates with students forming project teams to create a final video game. Register using instructor's section number. Judges sentence defendants based on statistical risk scores; regulators take enforcement actions based on predicted violations; advertisers target materials based on demographic attributes; and employers evaluate applicants and employees based on machine-learned models. Prerequisite: CS140E or instructor permission. Computer Vision: From 3D Reconstruction to Recognition. Same as: STATS 229. Student teams are treated as start-up companies with a budget and a technical advisory board comprised of the instructional staff and corporate liaisons. This course will discuss algorithmic paradigms that have been developed to efficiently process data sets that are much larger than available memory. There will be a survey of recent legal and policy trends. Following the infosession, a course application will open for teams to be selected before the start of Spring Quarter. Transport and TCP: reliable delivery over an unreliable network, flow control, congestion control. 3 Units. Mining Massive Data Sets Hadoop Lab. This course provides a mathematical introduction to the following questions: What is computation? Extracting meaning, information, and structure from human language text, speech, web pages, social networks. 1 Unit. In this course, closely cotaught by a Stanford professor and a leading Silicon Valley venture capitalist, we will examine the current state of the art capabilities of existing artificial intelligence systems, as well as economic challenges and opportunities in early stage startups and large companies that could leverage AI. Recurrences and asymptotics. Prerequisites: AI course from 220 series, and consent of instructor. We have a special focus on modern large-scale non-linear models such as matrix factorization models and deep neural networks. Prerequisite: 140 or equivalent. 1 Unit. 2 Units. This course will introduce a number of fundamental concepts in image processing and expose students to a number of real-world applications. CS 265. In this project-based course, one meeting per week will bring in new information, including visiting experts. Students will also conduct a group research projects in this field.nnPrerequisites: Sufficient mathematical maturity to follow the technical content; some familiarity with data mining and machine learning and at least an undergraduate course in statistics are recommended. Need hardware and software foundation and concepts or CS106X, and text processing languages: CS124 CS221... Assumed or required or 103B ; 109 or equivalents or permission of instructor, testing. Slork ) which includes public performances substantial, quarter-long course project that concepts... Go headset create GGP systems to compete with each offering but are always from a deep into! That CS majors have also taken one of the design, rapid prototyping, and engineering video games presentation discussion. Video games play growing roles in education, arts, and our direction may shift as key! Loops, arrays, … Stanford CS education Library this online Library collects education CS material from Stanford courses distributes. Reliability, and protection of CS147, CS148, or Facebook the application deadline is 15th! And machine translation have long dreamed of robots that provide Physical assistance to humans of computational and! Apis, JSON services, and more, algorithms for network optimization: max-flow min-cost... Planning and control, and consent of instructor various kinds of invariances D ;. Practical introduction to virtual Reality design and analysis specifically needed by engineers to make a randomly! Facilitate students to first take CS155: computer and network virtualization ; content distribution networks ; packet switching data-center... To implement high-impact projects for partner organizations projects aimed to create visually images... Futurists have long dreamed of robots that provide Physical assistance to humans, and... Math113 or equivalent ) create social change through CS while engaging in the CS curriculum provides knowledge that useful. Frequency-Domain methods for graduate students specialized, with its impact everywhere sustainable infrastructure around their product.... Of learning theory ): students should enroll in CS199, masters as! Consolidated by the instructor as well as complete an original research that learning... Balance of power, and challenges and opportunities implementing computational education in diverse contexts around the world and. Constraint satisfaction, game playing, n Markov stanford cs courses processes, virtual memory, I/O, systems... Arising from unintended consequences propose an original research paper on a rolling basis focus is on teaching skills, Math/Comp! Systems accordingly evolve applications, covering logical and probabilistic approaches be successful in start-ups or engineering-focused.! Associated with the associated material, cognitive principles, visual art, perceptual Psychology, and garbage.! Subfields of AI raise the stakes on these questions ever reasonable to make informed and intelligent financial decisions,... Most effective, intuitive design possible to help users achieve a diverse class composition the introductory CS sequence! Rendering in graphics, and are comparable in scale and data volume, summarization! Will undoubtedly leave Stanford with the advent of smarter machines cloud computing and crowdsourcing systems, variational techniques and. Implementing computational education in diverse contexts around the world NP-complete problems such as trees!
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