Using Bits to Control Atoms. Optimization and Algorithmic Paradigms. This class is a graduate level research seminar featuring prominent researchers and industry practitioners working on different aspects of knowledge graphs. 2 Units. A physics / quantum mechanics background is not required. Topics include hashing, dimension reduction and LSH, boosting, linear programming, gradient descent, sampling and estimation, and an introduction to spectral techniques. Advanced undergraduate or masters level work in mathematics and statistics will provide a good background for the doctoral program. We will learn how to acquire, represent, edit and remix video. Project topics will be selected from a diverse array of computer graphics concepts and historical elements. In light of the current situation with the COVID-19 pandemic, Stanford reaffirms its commitment to perform individualized, holistic review of each applicant to its graduate and professional programs. CS 197. Jyv skyl : Jyv skyl. CS 254 recommended but not required. Campus Map Principles of web security. Supervised Undergraduate Research. and inform future choices (can we use historical electronic medical records data about decision made and outcomes, to create better protocols to enhance patient health?). Possible topics include but are not limited to, spectral graph theory, sparsification, oblivious routing, local partitioning, Laplacian system solving, and maximum flow. Computational Social Choice. Design of engineering systems within a formal optimization framework. Students will be introduced to the Unreal editor, game frameworks, physics, AI, multiplayer and networking, UI, and profiling and optimization. ... Stanford engineers, computer scientists, data scientists, mathematicians and other professionals are building systems for lending, investment and portfolio management decisions that determine future economic and social growth. This project-based course will give creative students an opportunity to work together on revolutionary change leveraging blockchain technology. Several pre-vetted and approved projects from the Stanford School of Medicine will be available for students to select from and build. The student’s adviser has primary responsibility for the adequacy of the program, which is subject to review by the Student Services Office. 3 Units. How will society respond as versatile robots and machine-learning systems displace an ever-expanding spectrum of blue- and white-collar workers? Simultaneously, we will explore the longer term societal impact of AI driven by inexorable trends in technology and entrepreneurship. Register using instructor's section number. Prerequisites: CS 103 or 103B. Introduction to Computing Principles. All courses taken for this requirement must be taken on a letter grade basis for three or more units. This course provides a survey of the most important and influential concepts in autonomous robotic manipulation. The course will cover the technical aspects of cryptocurrencies, blockchain technologies, and distributed consensus. Courses counted as math electives cannot also count as CS electives, and vice versa. Prerequisites: CS 107, CS 109, CS 161. We plan to have a weekly seminar speaker to discuss issues such as verification of AI systems, reward misalignment and hacking, secure and attack-resilient AI systems, diagnosis and repair, issues regarding policy and ethics, as well as the implications of AI safety in automotive industry. The Mathematics, Science, and Engineering Fundamentals requirements are non-standard for this track. For students whose principal interest is an exposure to the fundamental ideas behind computer science and programming, CS 101 or CS 105 are the most appropriate courses. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. CS 448B. The first year of the Ph.D. program is spent working with 1-3 different professors on a rotating basis. Students will learn how these systems work and how to engineer secure software that interacts with the Bitcoin network and other cryptocurrencies. in CS with distinction in research must first identify a faculty adviser who agrees to supervise and support the research work. Attend a weekly honors seminar Winter Quarter. Topics covered include: the C programming language, data representation, machine-level code, computer arithmetic, elements of code compilation, memory organization and management, and performance evaluation and optimization. Qualified computer science students engage in internship work and integrate that work into their academic program. University requirements for the coterminal master’s degree are described in the “Coterminal Master’s Program” section. Over the years, many powerful algorithms have been built via tools such as linear programming relaxations, spectral properties of graphs, and others, that all bridge the discrete and continuous worlds. 1 Unit. Prerequisites: CS250 / EE387 or EE388; or linear algebra and permission of the instructor. In a different vein, convex relaxations are a useful tool for graph partitioning problems; central to the analysis are metric embedding questions for certainly computationally defined metrics. The lab builds on the the theoretical and evidence-based foundations explored in the EDUC 236 / CS 402 Practicum. Developing applications for the iPhone and iPad requires integration of numerous concepts including functional programming, object-oriented programming, computer-human interfaces, graphics, animation, reactive interfaces, Model-View-Intent (MVI) and Model-View-View-Model (MVVM) design paradigms, object-oriented databases, networking, and interactive performance considerations including multi-threading. CS 339N. CS 348K. Special study under faculty direction, usually leading to a written report. Classic and new papers. Stanford’s joint degree in law and computer science echoes that collective experience. Mining Massive Data Sets Hadoop Lab. Topics vary. Interactive media and games increasingly pervade and shape our society. Introduction to the fundamental concepts of computer systems through bare metal programming on the Raspberry Pi. Departmental Lecture Series. Special study under faculty direction, usually leading to a written report. At least 36 of these must be graded units, passed with a grade point average (GPA) of 3.0 (B) or better. Seminar covering issues in natural language processing related to ethical and social issues and the overall impact of these algorithms on people and society. Students work on an existing project of their own or join one of these projects. In the final 3-4 weeks of the class, teams will participate in an open-ended design challenge. Same as: EDUC 211. The program trains students in the tools of modern epidemiology, with heavy emphases on statistics, computer science, genetics, genomics, and bioinformatics. CS 49N. Prerequisites: BIOMEDIN 210 or 214 or 215 or 217 or 260. This course will introduce the probabilistic approach to cognitive science, in which learning and reasoning are understood as inference in complex probabilistic models. A follow up class to CS106A for non-majors which will both provide practical web programming skills and cover essential computing topics including computer security and privacy. Not a programming course. We will also examine the ethical consequences of design decisions and explore current issues arising from unintended consequences. In this master’s program, courses taken during or after the first quarter of the sophomore year are eligible for consideration for transfer to the graduate career; the timing of the first graduate quarter is not a factor. nnRequired Prerequisites: CS131A, CS231A, CS231B, or CS231N. CS 358. Methods for animating virtual characters and crowds. CS 472. The Human Genome Source Code. CS 245. Restrictions: CS 157 and PHIL 151 may not be used in combination to satisfy the math electives requirement. Course will focus on actual industry-based financial information from technology companies and realistic financial issues. This is an implementation-heavy, lab-based class that continues the topics from CS240LX. Given class size limitations, an online survey will be used to achieve a diverse class composition. 3-4 Units. Students with little prior experience or those who wish to take more time to study the fundamentals of programming should take CS 106A followed by CS 106B. Same as: BIOMEDIN 371, BIOPHYS 371, CME 371. Encoding information in the form of logical sentences. 3 Units. CS 57N. Computer Systems from the Ground Up. Students should consult their department or program's student services office for applicability of Overseas Studies courses to a major or minor program. Most students planning to obtain the Ph.D. degree should apply directly for admission to the Ph.D. program. 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. Today¿s successful companies are those that most effectively generate, protect, and exploit new and valuable business ideas. Application is required. May be repeated for credit. Emphasis on discussing recent empirical findings, methods and theoretical debates in the field. Students must satisfy the requirements for both the J.D. 3 Units. The goal of the course is to introduce the variety of areas in which distributional shifts appear, as well as provide theoretical characterization and learning bounds for distribution shifts. 1 Unit. 3 Units. Advanced material is often taught for the first time as a topics course, perhaps by a faculty member visiting from another institution. Reasoning with information in this form. Classic papers, new ideas, and research papers in networking. Students may propose to the M.S. Advanced undergraduate or masters level work in mathematics and statistics will provide a good background for the doctoral program. CS 247G. CS 354. Prerequisites: 147 or equivalent background. Same as: MED 253. 3 Units. Student teams under faculty supervision work on research and implementation of a large project in AI. 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. degree in Computer Science is intended as a terminal professional degree and does not lead to the Ph.D. degree. Quantum computing is an emerging computational paradigm with vast potential. Thus, students are trained in basic science to understand what brings about the conditions for human flourishing and will create meaningful AI technologies that aligns with the PACE framework: 1) has a clear and meaningful purpose, 2) augments human dignity and autonomy, 3) creates a feeling of inclusivity and collaboration, 4) creates shared prosperity and a sense of forward movement (excellence). Consent Application for Non-Law Students: We will try to accommodate all students interested in the course. Students will learn to be part of a deadline-driven software development effort working to meet the needs of a theater director and creative specialists -- while communicating the effect of resource limits and constraints to a nontechnical audience. Concurrent enrollment in CS 109 required. Software Project Experience with Corporate Partners. Students enroll in the CS 294W section attached to the CS 294 project they have chosen. This course explores methods for modeling biomedical systems with an emphasis on contemporary semantic technology, including knowledge graphs. Many complex data can be represented as a graph of relationships between objects. Students will benefit from some background in deep learning (CS 230, CS 231N), computer vision (CS 231A), digital image processing (CS 232) or computer graphics (CS248). Students can replace one of these electives with a course found at: Track Electives: at least three additional courses from the lists above, the general CS electives list, or the courses listed below. Although FAccT will be difficult to achieve, emerging technical approaches in this topic show promise in making better FAccT AI systems. Basic principles for endowing mobile autonomous robots with perception, planning, and decision-making capabilities. In the frontiers of computer technology FAccT AI systems have spurred technological innovation and, in which the team... Your dissertation and fun exploration of great ideas from computational genomics, machine learning hardware-software interactions same. Hired to staff teaching and research assistantships quarter-long design project, supported by lectures, readings, and these... A proposal of a final paper more efficiently application projects include writing security exploits defending... 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