Letter grade; if not appropriate, enroll in CS399P. Class is open to students of all years. Admissions: email@example.com. This course will deep dive into user interface design across mobile, desktop, and wearable platforms covering common patterns, when to use them, and when to break them. What if he has a PhD? This project-based course provides an introduction to game design principals while applying them to games that teach. Visit the Graduate Student Gateway for information about enrollment, financial aid, housing and more. Prerequisites: Basic knowledge about machine learning from at least one of CS 221, 228, 229 or 230. The department offers many introductory courses to meet the needs of these students. The program prepares students for careers in government, law, and the corporate sector, and for graduate study. Departmental Lecture Series. Students complete weekly coding assignments reinforcing machine learning concepts and applications. Note that if CS145 was waived in area (A), students should take an additional course from either area (B) or (C) in its place. 4 Units. Students will read recent research papers and complete a design project. Group or individual projects under faculty direction. Programming Service Project. Course website: http://cs1u.stanford.edu. Detailed reading of 5 selected Ph.D. dissertations within a field of computer science. Same as: SYMSYS 195B. A student must complete 135 course units for graduation. CS 294S. Class covers the fundamentals in operational space dynamics and control, elastic planning, human motion synthesis. 3-5 Units. Same as: EE 368. Students are expected to create an original research paper on a related topic. Those students who have waived out of CS 221 may take an additional course in either area (B) or (C). Admission to the joint MSCS/MBA program requires that students apply and be accepted independently to both the Computer Science Department in the School of Engineering and the Graduate School of Business. Possible projects suggested by partner organizations will be presented at an information session in early March. Computational Complexity. (Previously numbered CS 369G.) Preference given to seniors. 3 Units. Prior knowledge of machine learning techniques, such as from CS 221, CS 229, CS 231N, STATS 202, or STATS 216 is required. This seminar will explore some of both the great discoveries that underlie computer science and the inventions that have produced the remarkable advances in computing technology. Geometric searching and optimization. Students will read and discuss published research papers as well as complete an original research project in small groups. Recommended: CS 106B, CS 42 or 142. A continuation of CS254 (Computational Complexity). Campus Map Student teams under faculty supervision work on research and implementation of a large project in AI. Prerequisites: Proficiency in Python; CS131 and CS229 or equivalents; MATH21 or equivalent, linear algebra. CS 106E. Prerequisite: CS 106B; recommended: CS161; consent of instructor for 3 units. Focus is on teaching skills, techniques, and final projects grading. Such networks are a fundamental tool for modeling complex social, technological, and biological systems. , 1999; mary lea & brian street, 2002; theresa lillis, 2004; for discussions of fallacies wasn t like your straight line oh this is achieved in text quirk et al. 3 Units. You will undoubtedly leave Stanford with the technical skills to excel in your first few jobs. This research-oriented course will first review and reveal the limitations (e.g., iid assumption on training and testing data, voluminous training data requirement, and lacking interpretability) of some widely used AI algorithms, including convolutional neural networks (CNNs), transformers, reinforcement learning, and generative adversarial networks (GANs). The course will concretize theories, concepts, and practices in weekly presentations (including examples) from industry experts with significant backgrounds and proven expertise in designing successful, evidence-based, educational technology products. The Graduate Admissions office will not be monitoring email during this time. Advanced Reading and Research. CS 237A. degree in Computer Science is intended as a terminal professional degree and does not lead to the Ph.D. degree. Research projects include Care for Senior at Senior Home, Surgical Quality Analysis, AI Assisted Parenting, Burn Analysis & Assessment and more. A survey of numerical approaches to the continuous mathematics used throughout computer science with an emphasis on machine and deep learning. This includes: goal-conditioned reinforcement learning techniques that leverage the structure of the provided goal space to learn many tasks significantly faster; meta-learning methods that aim to learn efficient learning algorithms that can learn new tasks quickly; curriculum and lifelong learning, where the problem requires learning a sequence of tasks, leveraging their shared structure to enable knowledge transfer. Documentation includes capture of project rationale, design and discussion of key performance indicators, a weekly progress log and a software architecture diagram. We will also discuss the applications of pseudrandomness to derandomization, cryptography and more. In this course, we will discuss several success stories at the intersection of algorithm design and machine learning, focusing on devising appropriate models and mathematical tools to facilitate rigorous analysis. Prerequisites: algorithms at the level of 212 or CS 161, probability at the level of 221, and basic game theory, or consent of instructor. In addition to Computer Science itself, Stanford offers several interdisciplinary degrees with a substantial computer science component. Students will have the opportunity to acquire their own video and implement the processing tools needed to computationally analyze and manipulate it. CS 187. Additional Topics in Teaching Computer Science. Student projects will identify an accessibility need, prototype a design solution, and conduct a user study with a person with a disability. 3 Units. Prerequisite: excellence in 106A or equivalent, or consent of instructor. Go to the Application Form. Explores how five concepts come together in computer systems: hardware, architecture, assembly code, the C language, and software development tools. Introduction to Computers. This is an implementation-heavy, lab-based class that covers similar topics as CS240, but by writing code versus discussing papers. Technology for Financial Systems. Sections are designed to allow students to acquire a deeper understanding of CS and its applications, work collaboratively, and develop a mastery of the material. Prerequisite: CS110. Prerequisites: programming ability at the level of CS 106A and familiarity with biology and statistics. Some biological background is helpful but not required. Deep learning and other methods for automatic speech recognition, speech synthesis, affect detection, dialogue management, and applications to digital assistants and spoken language understanding systems. CS + Social Good Studio: Designing Social Impact Projects. Natural Language Understanding. If students have fulfilled the six breadth-area requirements, and taken courses from at least four different faculty who are members of the Academic Council, they are eligible to apply for candidacy prior to the second year in the program. Recent breakthroughs in high-throughput genomic and biomedical data are transforming biological sciences into "big data" disciplines. Both the adviser and the advisee are expected to maintain professionalism and integrity. CS 257. The class is aimed toward students with experience in data science and AI, and will include guest lectures by biomedical experts. Applications for a minor in Computer Science are submitted at the same time as admission to candidacy. The lab builds on the the theoretical and evidence-based foundations explored in the EDUC 236 / CS 402 Practicum. Students must be co-enrolled in CS106B. Enrollment is restricted to seniors and coterminal students until January 4, 2021. A project-based course that builds on the introduction to design in CS147 by focusing on advanced methods and tools for research, prototyping, and user interface design. 3 Units. Practical experience in programming. Focus on modern standardized APIs and best practices. Prerequisites: 103, 110. The Mathematics, Science, and Engineering Fundamentals requirements are non-standard for this track. Guest computer scientist. 3 Units. Get started or continue work on your application today. Problem-solving Lab for CS109. Students should consult their department or program's student services office for applicability of Overseas Studies courses to a major or minor program. CS 298. We draw upon research in cognitive and systems neuroscience to take advantage of what is known about how humans communicate and solve problems in order to design advanced artificial neural network architectures. The fundamentals and state-of-the-art in web security. Main class components are workshops, community discussions, guest speakers and mentorship. CS 547. Overview of logic technology and its applications - in mathematics, science, engineering, business, law, and so forth. 3-4 Units. In this hands-on project-based course, students will learn about future opportunities and present realities for autonomous robots that provide physical assistance to humans. Campus Map See http://graphics.stanford.edu/courses for offererings and prerequisites. Recent notable lawsuits will be discussed, including Apple v. Samsung (patents), Alice Corp. v. CLS Bank (software and business method patents), Oracle v. Google (software/APIs), Waymo v. Uber (civil and criminal trade secret theft), and hiQ v. LinkedIn (CFAA). Other topics include correlation decay in spin systems, variational techniques, holographic algorithms, and polynomial interpolation-based counting. Statistics, computer science, optimization, economics, sociology, and possibly other social sciences. CS 270. Readings will include classic papers along with additional explanatory material. Computation and Cognition: The Probabilistic Approach. Computers, Ethics, and Public Policy. degree as specified in this Bulletin. Research Project in Software Systems and Security. Programming Language Foundations. CS 111 and CS 140 cannot both be counted towards the BS requirements. 3 Units. Advanced reading and research for CS PhD students. CS 264. In particular, we will cover concepts and phenomenon such as uniform convergence, double descent phenomenon, implicit regularization, and problems such as matrix completion, bandits, and online learning (and generally sequential decision making under uncertainty). CS 47. Cryptocurrencies and blockchain technologies. This course will introduce the probabilistic approach to cognitive science, in which learning and reasoning are understood as inference in complex probabilistic models. Same as: VPTL 196. Students are expected to be able to: The purpose of the master’s program is to provide students with the knowledge and skills necessary for a professional career or doctoral studies. Additional problem solving practice for the introductory CS course CS107. The intent is to allow the first-year Ph.D. student to work with a variety of professors before aligning with a permanent program adviser. to design educational toolkits, educational toys, science kits, and tangible user interfaces. 3-5 Units. In addition to being admitted separately to the Law School and the Computer Science Department, students must secure permission from both academic units to pursue degrees in those units as part of a joint degree program. Prerequisite: 253 or consent of instructor. What does it mean to design for AI? Same as: WIM. Same as: LINGUIST 188, LINGUIST 288, SYMSYS 195U. CS 359. Prerequisite: experience in C/C++ and/or Java.See https://ccrma.stanford.edu/courses/256a/. Prerequisite: CS 106A or equivalent knowledge of coding. This course covers the architecture of modern data storage and processing systems, including relational databases, cluster computing frameworks, streaming systems and machine learning systems. Prerequisites: MATH 51; Math104 or MATH113 or equivalent or comfort with the associated material. Same as: MUSIC 253. Possible topics include advanced C++ language features, standard libraries, STL containers and algorithms, templates, object memory management, operator overloading, and move semantics. Topics in Programming Language Theory. 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. Prerequisite: 107. Introduction to Cryptography. Topics include major image databases, fundamental methods in image processing and quantitative extraction of image features, structured recording of image information including semantic features and ontologies, indexing, search and content-based image retrieval. CS 522. But non-technical skills are just as critical to making a difference. Weekly speakers on human-computer interaction topics. Students pursuing this joint degree must have at least basic training or experience in computer science. Students can replace one of these electives with a course found at. Advanced Multi-Core Systems. For example, what is the value of a new dataset or an improved algorithm? Great Ideas in Computer Science Covers the intellectual tradition of computer science emphasizing ideas that reflect the most important milestones in the history of the discipline. in Computer Science must apply for admission to the Computer Science Department either (i) concurrently with applying to the Law School; or (ii) after being admitted to the Law School, but no later than the earlier of: (a) the end of the second year of Law School; or (b) the Computer Science Department's admission deadline for the year following that second year of Law School. CS 422. It is the university's home for fundamental research, where free, open, and critical inquiry is pursued across disciplines. Same as: CME 309. The student must pass a University oral examination in the form of a defense of the dissertation. By Spring Quarter of the third year, a student should pass a, Within one year of passing the Qualifying Examination, a student should form a Reading Committee and submit a signed, By Spring Quarter of the fourth year, a student should schedule a Thesis Proposal with the reading committee members and submit the. CS 448B. Advanced Survey of Reinforcement Learning. CS 399P. 3-4 Units. Enrollment limited and application required. 11. 1 Unit. Prerequisites: CS161 or equivalent, STAT116 or equivalent. This course will introduce students interested in computer science, engineering, and media to what is possible and probable when it comes to media innovation. Topics in Analysis of Algorithms. Prerequisites: ECON 203 or equivalent. CS 275. 10% of its graduate students are part-time graduate students. For the first time, a joint Stanford Computer Science MS/MBA degree program will be available to graduate students in the 2014-2015 academic year. Pseudorandomness is the widely applicable theory of efficiently generating objects that look random, despite being constructed using little or no randomness. Applications range from the design of aircraft to automated vehicles. CS 182W. Students who meet the eligibility requirements and wish to be considered for the honors program must submit a written application to the CS undergraduate program office by May 1 of the year preceding the honors work. Margaret Jacks Hall Building 460 Stanford University Stanford, CA 94305-2150. Additional problem solving practice for the introductory CS course CS109. Apply the knowledge of mathematics, science, and engineering. Same as: EE 387. The course is open to students who have completed the introductory CS course sequence through 110. The target participants are advanced undergrads as well as MS students with interest in CS theory. But that's muscle. This seminar is taught by two industry veterans in engineering leadership and product management. Topics include redundancy, inertial properties, haptics, simulation, robot cooperation, mobile manipulation, human-friendly robot design, humanoids and whole-body control. Grading based primarily on student projects. A maximum of 6 units of independent study (. CS 247I. Students will read and take turns presenting current works, and they will produce a proposal of a feasible next research direction. Information Retrieval and Web Search. Prerequisites: Appropriate preparation depends on the nature of the project proposed, and will be verified by the teaching staff based on your application. 3 Units. We will also examine the ethical consequences of design decisions and explore current issues arising from unintended consequences. Some students, however, may wish to complete the master's program before deciding whether to pursue the Ph.D. Prerequisite: linear algebra. CS 106M. Computer Systems from the Ground Up. CS 106L. Topics include: Big data systems (Hadoop, Spark); Link Analysis (PageRank, spam detection); Similarity search (locality-sensitive hashing, shingling, min-hashing); Stream data processing; Recommender Systems; Analysis of social-network graphs; Association rules; Dimensionality reduction (UV, SVD, and CUR decompositions); Algorithms for large-scale mining (clustering, nearest-neighbor search); Large-scale machine learning (decision tree ensembles); Multi-armed bandit; Computational advertising. Digital Image Processing. Same as: AA 289. Problem solving strategies and techniques in discrete mathematics and computer science. The course will consist of group and individual work and encourages creativity. Supervised Undergraduate Research. In addition to their dominant roles in entertainment, video games play growing roles in education, arts, and science. How do we design these social computing systems to be effective and responsible? CS 340LX. CS107 and CS110 recommended. Topics include type systems (polymorphism, algebraic data types, static vs. dynamic), control flow (exceptions, continuations), concurrency/parallelism, metaprogramming, and the semantic gap between computational models and modern hardware. Students will learn the model of quantum computation, quantum programming languages, hybrid quantum/classical programming, quantum algorithms, quantum error correction, and applications. The math electives list consists of: MATH 51, MATH 52, MATH 53, MATH 104, MATH 107, MATH 108, MATH 109, MATH 110, MATH 113; CS 157, CS 205L, PHIL 151; CME 100, CME 102, CME 104, ENGR 108. CS 499. Introduces fundamental methods and principles for designing, implementing, and evaluating user interfaces. While understanding users is one part of the equation, the other part is a strong understanding of user interface design rules and patterns that you can apply to solve their needs. It is based on decades of observations by the instructors, witnessing that fresh graduates routinely struggle to survive and create an impact in the corporate world. This course covers the fundamentals of functional programming and algebraic type systems, and explores a selection of related programming paradigms and current research. The focus of CS247S is Service Design. The fundamentals of cross-platform mobile application development using the React Native framework (RN). This course is designed as a deep dive into the design, analysis, implementation, and theory of data structures. Systems, and Theoretical Computer Science; M.S. Visual computing tasks such as computational photography, image/video understanding, and real-time 3D graphics are key responsibilities of modern computer systems ranging from sensor-rich smart phones, autonomous robots, and large data centers. Prerequisite: CS106A or equivalent programming experience. This course surveys the legal and ethical principles for assessing the equity of algorithms, describes statistical techniques for designing fair systems, and considers how anti-discrimination law and the design of algorithms may need to evolve to account for machine bias. Advanced Topics in Formal Methods. Provides paradigms and strategies for designing and building music software, with emphases on interactive systems, aesthetics, and artful product design. The Departments of Computer Science and Philosophy offer a joint major program (JMP) for undergraduates who wish to gain mastery and develop skills in these two disciplines. In an always-on, tech-driven world, how do we regain control over our wellbeing?nThis 1 unit course is part workshop, part seminar, with a focus on tackling and re-framing the relationship between technology and wellness. What role will they play in our system of justice and the practice of law? Today we interact with our friends and enemies, our team partners and romantic partners, and our organizations and societies, all through computational systems. An introduction to computational complexity theory. 3-4 Units. A Linux or Mac laptop that you are comfortable coding on. Each week consists of in-class activities designed by student groups, local tech companies, and nonprofits. CS 402L. Bare-metal lets us do interesting tricks without constantly fighting a lumbering, general-purpose OS that cannot get out of its own way. The following are general department requirements. Enrollment requires instructor permission. CS 229M. To this end, a growing body of work in both industry and academia leverages formal methods techniques to solve computer systems challenges. Application required; please see cs51.stanford.edu for more information. Topics vary every quarter, and may include advanced material being taught for the first time. For the first time, a joint Stanford Computer Science MS/MBA degree program will be available to graduate students in the 2014-2015 academic year. Examples will be drawn from areas including concept learning, causal reasoning, social cognition, and language understanding. Prerequisites: knowledge of linear algebra, discrete probability and algorithms. How do we use mathematical thinking to design better machine learning methods? Each week will cover a different user interface design challenge and explore the patterns in areas such as data input, search & filters, tables and lists, content organization, navigation, dark patterns and more. CS 103A. Importantly, we will respect decisions regarding the adoption of Credit/No Credit and other grading options during this unprecedented period of COVID-19 disruption, whether they are made by institutions or by individual students. Independent Project. Wellness in Tech: Designing an Intentional Lifestyle in a Tech-Driven World. Alumni of the course are given the opportunity to be connected to faculty for ongoing research, or to repeat the class under CS197A for credit (but no lecture component) to continue work on their projects. Topics: user-centered design, rapid prototyping, experimentation, direct manipulation, cognitive principles, visual design, social software, software tools. We will cover the design of accelerators for ML model inference and training. Natural Language Processing with Deep Learning. May be repeated for credit. Recommended: CS 148 and/or 205A. Quantitative (e.g. Same as: STATS 229. Educational opportunities in high technology research and development labs in the computing industry. Beyond Bits and Atoms - Lab. Email: firstname.lastname@example.org. Contact the Computer Science Ph.D. administrator for details. Phone: (650) 723-2300 Admissions: email@example.com. By the end of the course, students should be able to understand andnimplement the state-of-the-art multi-task learning algorithms and be ready to conduct research on these topics. Introduction to Computer Graphics and Imaging. Prerequisite: consent of instructor. Same as: MS&E 336. Some projects may relate to CS department research. Must first stanford phd computer science a faculty member visiting from another institution set of research approved from! Futurists have long dreamed of robots that provide Physical assistance to humans simple word and! Milestone, teams must demonstrate that their routers can interoperate with the computer Science and Electrical engineering deeply. Quarterly tuition for the Ph.D. degree should apply directly for admission to the unknown, and other! Cs240, but by writing code versus discussing papers to seniors and coterminal students until January 4, 2021 program... Law studies 106A uses Python as its programming language C++ covering its facilities... 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