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1 - 10 of 23 results for: CS ; Currently searching summer courses. You can expand your search to include all quarters

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CS 103: Mathematical Foundations of Computing

What are the theoretical limits of computing power? What problems can be solved with computers? Which ones cannot? And how can we reason about the answers to these questions with mathematical certainty? This course explores the answers to these questions and serves as an introduction to discrete mathematics, computability theory, and complexity theory. At the completion of the course, students will feel comfortable writing mathematical proofs, reasoning about discrete structures, reading and writing statements in first-order logic, and working with mathematical models of computing devices. Throughout the course, students will gain exposure to some of the most exciting mathematical and philosophical ideas of the late nineteenth and twentieth centuries. Specific topics covered include formal mathematical proofwriting, propositional and first-order logic, set theory, binary relations, functions (injections, surjections, and bijections), cardinality, basic graph theory, the pigeonhole prin more »
What are the theoretical limits of computing power? What problems can be solved with computers? Which ones cannot? And how can we reason about the answers to these questions with mathematical certainty? This course explores the answers to these questions and serves as an introduction to discrete mathematics, computability theory, and complexity theory. At the completion of the course, students will feel comfortable writing mathematical proofs, reasoning about discrete structures, reading and writing statements in first-order logic, and working with mathematical models of computing devices. Throughout the course, students will gain exposure to some of the most exciting mathematical and philosophical ideas of the late nineteenth and twentieth centuries. Specific topics covered include formal mathematical proofwriting, propositional and first-order logic, set theory, binary relations, functions (injections, surjections, and bijections), cardinality, basic graph theory, the pigeonhole principle, mathematical induction, finite automata, regular expressions, the Myhill-Nerode theorem, context-free grammars, Turing machines, decidable and recognizable languages, self-reference and undecidability, verifiers, and the P versus NP question. Students with significant proofwriting experience are encouraged to instead take CS154. Students interested in extra practice and support with the course are encouraged to concurrently enroll in CS103A. Prerequisite: CS106B or equivalent. CS106B may be taken concurrently with CS103.
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: GER:DB-Math, WAY-FR

CS 106A: Programming Methodology

Introduction to the engineering of computer applications emphasizing modern software engineering principles: program design, decomposition, encapsulation, abstraction, and testing. Emphasis is on good programming style and the built-in facilities of respective languages. Uses the Python programming language. No prior programming experience required.
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: WAY-FR, GER:DB-EngrAppSci

CS 106B: Programming Abstractions

Abstraction and its relation to programming. Software engineering principles of data abstraction and modularity. Object-oriented programming, fundamental data structures (such as stacks, queues, sets) and data-directed design. Recursion and recursive data structures (linked lists, trees, graphs). Introduction to time and space complexity analysis. Uses the programming language C++ covering its basic facilities. Prerequisite: 106A or equivalent.
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: GER:DB-EngrAppSci, WAY-FR

CS 107: Computer Organization and Systems

Introduction to the fundamental concepts of computer systems. Explores how computer systems execute programs and manipulate data, working from the C programming language down to the microprocessor. 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. Prerequisites: 106B or X, or consent of instructor.
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: WAY-FR, GER:DB-EngrAppSci

CS 109: Introduction to Probability for Computer Scientists

Topics include: counting and combinatorics, random variables, conditional probability, independence, distributions, expectation, point estimation, and limit theorems. Applications of probability in computer science including machine learning and the use of probability in the analysis of algorithms. Prerequisites: 103, 106B or X, multivariate calculus at the level of MATH 51 or CME 100 or equivalent.
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: WAY-AQR, WAY-FR, GER:DB-EngrAppSci

CS 148: Introduction to Computer Graphics and Imaging

This is the introductory, prerequisite course in the computer graphics sequence that introduces students to the technical concepts behind creating computer generated images. Through this course, students will gain a firm working knowledge of the underlying mathematical concepts of synthetic imagery (including triangles, meshes, normals, interpolation, world spaces, texture mapping, etc.) Students will also explore the fundamentals of light and color and how they interact with the environment through lighting, shading, and material models varying in realism and complexity. Ultimately, students will come to an understanding of rasterization and ray tracing technology for creating visually-compelling synthetic images, and briefly examine how they extend to animation and inverse rendering. Students will additionally be exposed to a high-level survey of topics in computer graphics, such as acceleration structures, anti-aliasing, and depth of field. Starter code will be provided to guide students through development and give them familiarity with industry-level tools. The class will conclude with a final project in which students pursue in-depth a specific topic of interest.nPrerequisites: Linear Algebra and familiarity with Python and debugging.
Terms: Aut, Sum | Units: 3-4 | UG Reqs: GER:DB-EngrAppSci, WAY-CE

CS 161: Design and Analysis of Algorithms

Worst and average case analysis. Recurrences and asymptotics. Efficient algorithms for sorting, searching, and selection. Data structures: binary search trees, heaps, hash tables. Algorithm design techniques: divide-and-conquer, dynamic programming, greedy algorithms, amortized analysis, randomization. Algorithms for fundamental graph problems: minimum-cost spanning tree, connected components, topological sort, and shortest paths. Possible additional topics: network flow, string searching. Prerequisite: 106B or 106X; 103 or 103B; 109 or STATS 116.
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: GER:DB-EngrAppSci, WAY-FR

CS 191: Senior Project

Restricted to Computer Science students. Group or individual research projects under faculty direction. Register using instructor's section number. A project can be either a significant software application or publishable research. Software application projects include a research component, substantial programming, and are comparable in scale to shareware programs or commercial applications. Research projects may result in a paper publishable in an academic journal or presentable at a conference. Public presentation of final application or research results is required. Prerequisite: Completion of at least 135 units and consent of instructor. Project proposal form is required before the beginning of the quarter of enrollment: https://cs.stanford.edu/degrees/undergrad/Senior%20Project%20Proposal.pdfhttps:// cs.stanford.edu/degrees/undergrad/Senior%20Project%20Proposal.pdf
Terms: Aut, Win, Spr, Sum | Units: 1-6 | Repeatable for credit
Instructors: Achour, S. (PI) ; Agrawala, M. (PI) ; Aiken, A. (PI) ; Altman, R. (PI) ; Angst, R. (PI) ; Bailis, P. (PI) ; Batzoglou, S. (PI) ; Bejerano, G. (PI) ; Bernstein, M. (PI) ; Blikstein, P. (PI) ; Bohg, J. (PI) ; Boneh, D. (PI) ; Borenstein, J. (PI) ; Bouland, A. (PI) ; Boyd, S. (PI) ; Cain, J. (PI) ; Cao, P. (PI) ; Charikar, M. (PI) ; Cheriton, D. (PI) ; Dally, B. (PI) ; Dill, D. (PI) ; Dror, R. (PI) ; Durumeric, Z. (PI) ; Engler, D. (PI) ; Ermon, S. (PI) ; Fatahalian, K. (PI) ; Fedkiw, R. (PI) ; Feigenbaum, E. (PI) ; Fikes, R. (PI) ; Finn, C. (PI) ; Fisher, K. (PI) ; Fogg, B. (PI) ; Follmer, S. (PI) ; Fox, A. (PI) ; Fox, E. (PI) ; Garcia-Molina, H. (PI) ; Genesereth, M. (PI) ; Girod, B. (PI) ; Goel, A. (PI) ; Goel, S. (PI) ; Goodman, N. (PI) ; Gregg, C. (PI) ; Guibas, L. (PI) ; Haber, N. (PI) ; Hanrahan, P. (PI) ; Hennessy, J. (PI) ; Horowitz, M. (PI) ; Icard, T. (PI) ; James, D. (PI) ; Johari, R. (PI) ; Jurafsky, D. (PI) ; Katti, S. (PI) ; Kay, M. (PI) ; Khatib, O. (PI) ; Kjoelstad, F. (PI) ; Kochenderfer, M. (PI) ; Koller, D. (PI) ; Koyejo, S. (PI) ; Kozyrakis, C. (PI) ; Kundaje, A. (PI) ; Lam, M. (PI) ; Landay, J. (PI) ; Latombe, J. (PI) ; Lee, C. (PI) ; Leskovec, J. (PI) ; Levis, P. (PI) ; Levitt, M. (PI) ; Levoy, M. (PI) ; Li, F. (PI) ; Liang, P. (PI) ; Liu, K. (PI) ; Ma, T. (PI) ; Manning, C. (PI) ; Mazieres, D. (PI) ; McCarthy, J. (PI) ; McKeown, N. (PI) ; Mirhoseini, A. (PI) ; Mitchell, J. (PI) ; Mitra, S. (PI) ; Montanari, A. (PI) ; Musen, M. (PI) ; Nayak, P. (PI) ; Ng, A. (PI) ; Niebles Duque, J. (PI) ; Olukotun, O. (PI) ; Ousterhout, J. (PI) ; Paepcke, A. (PI) ; Pande, V. (PI) ; Parlante, N. (PI) ; Pea, R. (PI) ; Piech, C. (PI) ; Plotkin, S. (PI) ; Plummer, R. (PI) ; Poldrack, R. (PI) ; Potts, C. (PI) ; Prabhakar, B. (PI) ; Pratt, V. (PI) ; Raghavan, P. (PI) ; Rajaraman, A. (PI) ; Re, C. (PI) ; Reingold, O. (PI) ; Roberts, E. (PI) ; Rosenblum, M. (PI) ; Roughgarden, T. (PI) ; Rubin, D. (PI) ; Sadigh, D. (PI) ; Sahami, M. (PI) ; Salisbury, J. (PI) ; Savarese, S. (PI) ; Saxena, A. (PI) ; Schwarz, K. (PI) ; Shoham, Y. (PI) ; Sosic, R. (PI) ; Stamos, A. (PI) ; Subramonyam, H. (PI) ; Tan, L. (PI) ; Thrun, S. (PI) ; Tobagi, F. (PI) ; Trippel, C. (PI) ; Ullman, J. (PI) ; Valiant, G. (PI) ; Van Roy, B. (PI) ; Vitercik, E. (PI) ; Wang, G. (PI) ; Wetzstein, G. (PI) ; Widom, J. (PI) ; Wiederhold, G. (PI) ; Winograd, T. (PI) ; Winstein, K. (PI) ; Wodtke, C. (PI) ; Wootters, M. (PI) ; Wu, J. (PI) ; Yamins, D. (PI) ; Yang, D. (PI) ; Yeung, S. (PI) ; Young, P. (PI) ; Zaharia, M. (PI) ; Zelenski, J. (PI) ; Zou, J. (PI)

CS 192: Programming Service Project

Restricted to Computer Science students. Appropriate academic credit (without financial support) is given for volunteer computer programming work of public benefit and educational value. Register using the section number associated with the instructor. Prerequisite: consent of instructor.
Terms: Aut, Win, Spr, Sum | Units: 1-4 | Repeatable for credit
Instructors: Achour, S. (PI) ; Aiken, A. (PI) ; Altman, R. (PI) ; Batzoglou, S. (PI) ; Bejerano, G. (PI) ; Bernstein, M. (PI) ; Boneh, D. (PI) ; Bouland, A. (PI) ; Cain, J. (PI) ; Cao, P. (PI) ; Cheriton, D. (PI) ; Dally, B. (PI) ; Dill, D. (PI) ; Engler, D. (PI) ; Fedkiw, R. (PI) ; Feigenbaum, E. (PI) ; Fikes, R. (PI) ; Finn, C. (PI) ; Fisher, K. (PI) ; Fogg, B. (PI) ; Fox, A. (PI) ; Garcia-Molina, H. (PI) ; Genesereth, M. (PI) ; Girod, B. (PI) ; Goel, A. (PI) ; Gregg, C. (PI) ; Guibas, L. (PI) ; Hanrahan, P. (PI) ; Hennessy, J. (PI) ; Horowitz, M. (PI) ; Johari, R. (PI) ; Jurafsky, D. (PI) ; Katti, S. (PI) ; Kay, M. (PI) ; Khatib, O. (PI) ; Koller, D. (PI) ; Kozyrakis, C. (PI) ; Lam, M. (PI) ; Latombe, J. (PI) ; Leskovec, J. (PI) ; Levis, P. (PI) ; Levitt, M. (PI) ; Levoy, M. (PI) ; Li, F. (PI) ; Manning, C. (PI) ; Mazieres, D. (PI) ; McCarthy, J. (PI) ; McKeown, N. (PI) ; Mitchell, J. (PI) ; Musen, M. (PI) ; Nayak, P. (PI) ; Ng, A. (PI) ; Olukotun, O. (PI) ; Ousterhout, J. (PI) ; Parlante, N. (PI) ; Plotkin, S. (PI) ; Plummer, R. (PI) ; Prabhakar, B. (PI) ; Pratt, V. (PI) ; Raghavan, P. (PI) ; Rajaraman, A. (PI) ; Roberts, E. (PI) ; Rosenblum, M. (PI) ; Roughgarden, T. (PI) ; Sahami, M. (PI) ; Salisbury, J. (PI) ; Schwarz, K. (PI) ; Shoham, Y. (PI) ; Thrun, S. (PI) ; Tobagi, F. (PI) ; Ullman, J. (PI) ; Van Roy, B. (PI) ; Widom, J. (PI) ; Wiederhold, G. (PI) ; Winograd, T. (PI) ; Wu, J. (PI) ; Yeung, S. (PI) ; Young, P. (PI) ; Zelenski, J. (PI)

CS 193C: Client-Side Internet Technologies

Client-side technologies used to create web sites such as Google maps or Gmail. Includes HTML5, CSS, JavaScript, the Document Object Model (DOM), and Ajax. Prerequisite: programming experience at the level of CS106A.
Terms: Sum | Units: 3
Instructors: Young, P. (PI)
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