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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 197C: Computer Science Research: CURIS Internship Onramp

A version of CS 197 designed specifically for students who will be participating in spring/summer CURIS internships OR have an ongoing research project with a (Ph.D. student or professor) mentor in the Stanford Computer Science department. 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 mentorship and feedback from the CURIS or research mentor on a real research project. Students will attend the same lectures as CS197 and may enroll for 3 units. Lecture topics include reading technical papers, practicing oral communication and technical writing skills, and independently formulating research questions. Students must have commitment from their CURIS or research mentor for weekly check-in meetings. Prerequisite: CS106B.
Terms: Spr | Units: 3
Instructors: Miranda, B. (PI)

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 202: Law for Computer Science Professionals

Businesses are built on ideas. Today's successful companies are those that most effectively generate, protect, and exploit new and valuable business ideas. Over the past 40 years, intellectual capital has emerged as the leading assets class. Ocean Tomo® estimates that over 80% of the market value of S&P 500 corporations now stems from intangible assets, which consist largely of intellectual property (IP) assets (e.g., the company and product names, logos and designs; patentable inventions; proprietary software and databases, and other proprietary product, manufacturing and marketing information). It is therefore vital for entrepreneurs and other business professionals to have a basic understanding of IP and how it is procured, protected, and exploited. This course provides an overview of the many and varied IP issues that students will confront during their careers. It is intended to be both informative and fun. Classes will cover the basics of patent, trademark, copyright, and trade secret law. Current issues in these areas will be covered, including patent protection for software and business methods, copyrightability of computer programs and APIs, issues relating to artificial intelligence, and the evolving protection for trademarks and trade secrets. Emerging issues concerning the federal Computer Fraud & Abuse Act (CFAA) and hacking will be covered, as will employment issues, including employee proprietary information and invention assignment agreements, work made for hire agreements, confidentiality agreements, non-compete agreements and other potential post-employment restrictions. 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). IP law evolves constantly and new headline cases that arise during the term are added to the class discussion. Guest lectures typically include experts on open source software; legal and practical issues confronted by business founders; and, consulting and testifying as an expert in IP litigation. Although many of the issues discussed will involve technology disputes, the course also covers IP issues relating to art, music, photography, and literature. Classes are presented in an open discussion format and they are designed to be enjoyed by students of all backgrounds and areas of expertise.
Terms: Spr | Units: 1
Instructors: Hansen, D. (PI)

CS 204: Computational Law

Computational Law is an innovative approach to legal informatics concerned with the representation of regulations in computable form. From a practical perspective, Computational Law is important as the basis for computer systems capable of performing useful legal calculations, such as compliance checking, legal planning, and regulatory analysis. In this course, we look at the theory of Computational Law, we review relevant technology and applications, we discuss the prospects and problems of Computational Law, and we examine its philosophical and legal implications. Work in the course consists of reading, class discussion, and practical exercises.
Last offered: Spring 2023

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)
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