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CS 197: Computer Science Research

An onramp for students interested in breaking new ground in the frontiers of computer science. Course format features faculty lectures introducing the fundamentals of computer science research, alongside special interest group meetings that provide mentorship and feedback on a real research project. Lecture topics include reading technical papers, practicing oral communication and technical writing skills, and independently formulating research questions. Any student may enroll for 4 units and select a research area (AI, HCI, Systems, etc.) for a quarter-long team programming project with a Ph.D. student mentor. Space may be limited. Prerequisite: CS106B.
Terms: Aut, Win, Spr | Units: 3-4

CS 198: Teaching Computer Science

Students lead a discussion section of 106A while learning how to teach a programming language at the introductory level. Focus is on teaching skills, techniques, and course specifics. Application and interview required; see http://cs198.stanford.edu.
Terms: Aut, Win, Spr | Units: 3-4

CS 198B: Additional Topics in Teaching Computer Science

Students build on the teaching skills developed in CS198. Focus is on techniques used to teach topics covered in CS106B. Prerequisite: successful completion of CS198.
Terms: Aut, Win, Spr | Units: 1

CS 199: Independent Work

Special study under faculty direction, usually leading to a written report. Register using instructor's section number. Letter grade; if not appropriate, enroll in CS199P. Prerequisite: consent of instructor.
Terms: Aut, Win, Spr, Sum | Units: 1-6 | Repeatable for credit
Instructors: Achour, S. (PI) ; Adeli, E. (PI) ; Agrawala, M. (PI) ; Aiken, A. (PI) ; Altman, R. (PI) ; Anari, N. (PI) ; Bailis, P. (PI) ; Barrett, C. (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) ; Brunskill, E. (PI) ; Cain, J. (PI) ; Cao, P. (PI) ; Chang, M. (PI) ; Charikar, M. (PI) ; Cheriton, D. (PI) ; Dally, B. (PI) ; Demszky, D. (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) ; Fox, A. (PI) ; Fox, E. (PI) ; Ganguli, S. (PI) ; Genesereth, M. (PI) ; Girod, B. (PI) ; Goel, A. (PI) ; Goodman, N. (PI) ; Gregg, C. (PI) ; Grimes, A. (PI) ; Guibas, L. (PI) ; Haber, N. (PI) ; Hanrahan, P. (PI) ; Hashimoto, T. (PI) ; Hennessy, J. (PI) ; Ho, D. (PI) ; Horowitz, M. (PI) ; Icard, T. (PI) ; James, D. (PI) ; Johari, R. (PI) ; Jurafsky, D. (PI) ; Katti, S. (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) ; Lin, H. (PI) ; Liu, K. (PI) ; Manning, C. (PI) ; Mazieres, D. (PI) ; McKeown, N. (PI) ; Mirhoseini, A. (PI) ; Mitchell, J. (PI) ; Mitra, S. (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) ; Patrignani, M. (PI) ; Pavone, M. (PI) ; Pea, R. (PI) ; Piech, C. (PI) ; Plotkin, S. (PI) ; Plummer, 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) ; Rubin, D. (PI) ; Rubinstein, A. (PI) ; Sadigh, D. (PI) ; Sahami, M. (PI) ; Salisbury, J. (PI) ; Savarese, S. (PI) ; Saxena, A. (PI) ; Schwarz, K. (PI) ; Shoham, Y. (PI) ; Stanford, J. (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) ; Widom, J. (PI) ; Winograd, T. (PI) ; Winstein, K. (PI) ; Wodtke, C. (PI) ; Wootters, M. (PI) ; Wu, J. (PI) ; Yamins, D. (PI) ; Yan, L. (PI) ; Yang, D. (PI) ; Yeung, S. (PI) ; Young, P. (PI) ; Zaharia, M. (PI) ; Zelenski, J. (PI) ; Zou, J. (PI)

CS 199P: Independent Work

Special study under faculty direction, usually leading to a written report. Register using instructor's section number. CR/NC only, if not appropriate, enroll in CS199. Prerequisite: consent of instructor.
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) ; Barrett, C. (PI) ; Batzoglou, S. (PI) ; Bejerano, G. (PI) ; Bernstein, M. (PI) ; Blikstein, P. (PI) ; Boneh, D. (PI) ; Borenstein, J. (PI) ; Bouland, A. (PI) ; Brunskill, E. (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) ; Fedkiw, R. (PI) ; Feigenbaum, E. (PI) ; Fikes, R. (PI) ; Finn, C. (PI) ; Fisher, K. (PI) ; Fogg, B. (PI) ; Fox, A. (PI) ; Fox, E. (PI) ; Genesereth, M. (PI) ; Girod, B. (PI) ; Goel, A. (PI) ; Goodman, N. (PI) ; Grimes, A. (PI) ; Guibas, L. (PI) ; Hanrahan, P. (PI) ; Hashimoto, T. (PI) ; Hennessy, J. (PI) ; Horowitz, M. (PI) ; James, D. (PI) ; Johari, R. (PI) ; Jurafsky, D. (PI) ; Katti, S. (PI) ; Khatib, O. (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) ; Lin, H. (PI) ; Liu, K. (PI) ; Manning, C. (PI) ; Mazieres, D. (PI) ; McKeown, N. (PI) ; Mirhoseini, A. (PI) ; Mitchell, J. (PI) ; Mitra, S. (PI) ; Musen, M. (PI) ; Nayak, P. (PI) ; Ng, A. (PI) ; Olukotun, O. (PI) ; Ousterhout, J. (PI) ; Parlante, N. (PI) ; Pavone, M. (PI) ; Piech, C. (PI) ; Plotkin, S. (PI) ; Plummer, R. (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) ; Sahami, M. (PI) ; Salisbury, J. (PI) ; Savarese, S. (PI) ; Saxena, A. (PI) ; Schwarz, K. (PI) ; Shoham, Y. (PI) ; Socher, R. (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) ; Widom, J. (PI) ; Winograd, T. (PI) ; Winstein, K. (PI) ; Wodtke, C. (PI) ; Wootters, M. (PI) ; Wu, J. (PI) ; Yamins, D. (PI) ; Yan, L. (PI) ; Yang, D. (PI) ; Young, P. (PI) ; Zaharia, M. (PI) ; Zelenski, J. (PI) ; Zou, J. (PI)

CS 205L: Continuous Mathematical Methods with an Emphasis on Machine Learning

A survey of numerical approaches to the continuous mathematics used throughout computer science with an emphasis on machine and deep learning. Although motivated from the standpoint of machine learning, the course will focus on the underlying mathematical methods including computational linear algebra and optimization, as well as special topics such as automatic differentiation via backward propagation, momentum methods from ordinary differential equations, CNNs, RNNs, etc. Written homework assignments and (straightforward) quizzes focus on various concepts; additionally, students can opt in to a series of programming assignments geared towards neural network creation, training, and inference. (Replaces CS205A, and satisfies all similar requirements.) Prerequisites: Math 51; Math104 or MATH113 or equivalent or comfort with the associated material.
Terms: Win | Units: 3

CS 206: Exploring Computational Journalism (COMM 281)

This project-based course will explore the field of computational journalism, including the use of Data Science, Info Visualization, AI, and emerging technologies to help journalists discover and tell stories, understand their audience, advance free speech, and build trust. This course is repeatable for credit; enrollment priority given to students taking it for the first time.
Terms: Win | Units: 3 | Repeatable 3 times (up to 9 units total)
Instructors: Agrawala, M. (PI) ; Brenner, R. (PI) ; Tumgoren, S. (PI) ; Chiueh, D. (TA)

CS 210A: Software Project Experience with Corporate Partners

Two-quarter project course. Focus is on real-world software development. Corporate partners seed projects with loosely defined challenges from their R&D labs; students innovate to build their own compelling software solutions. Student teams are treated as start-up companies with a budget and a technical advisory board comprised of instructional staff and corporate liaisons. Teams will typically travel to the corporate headquarters of their collaborating partner, meaning some teams will travel internationally. Open loft classroom format such as found in Silicon Valley software companies. Exposure to: current practices in software engineering; techniques for stimulating innovation; significant development experience with creative freedoms; working in groups; real-world software engineering challenges; public presentation of technical work; creating written descriptions of technical work. Prerequisites: CS109 and CS161.
Terms: Win | Units: 3-4
Instructors: Borenstein, J. (PI) ; Saracay, E. (TA) ; Vo, N. (TA)

CS 212: Operating Systems and Systems Programming

Covers key concepts in computer systems through the lens of operatingsystem design and implementation. Topics include threads, scheduling,processes, virtual memory, synchronization, multi-core architectures,memory consistency, hardware atomics, memory allocators, linking, I/O,file systems, and virtual machines. Concepts are reinforced with fourkernel programming projects in the Pintos operating system. This classmay be taken as an accelerated single-class alternative to the CS111,CS112 sequence; conversely, the class should not be taken by studentswho have already taken CS111 or CS112.
Terms: Win | Units: 3-5

CS 223A: Introduction to Robotics (ME 320)

Robotics foundations in modeling, design, planning, and control. Class covers relevant results from geometry, kinematics, statics, dynamics, motion planning, and control, providing the basic methodologies and tools in robotics research and applications. Concepts and models are illustrated through physical robot platforms, interactive robot simulations, and video segments relevant to historical research developments or to emerging application areas in the field. Recommended: matrix algebra.
Terms: Win | Units: 3
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