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1 - 10 of 83 results for: CS ; Currently searching winter courses. You can expand your search to include all quarters

CS 1U: Practical Unix

A practical introduction to using the Unix operating system with a focus on Linux command line skills. Class will consist of video tutorials and weekly hands-on lab sections. The time listed on AXESS is for the first week's logistical meeting only. Topics include: grep and regular expressions, ZSH, Vim and Emacs, basic and advanced GDB features, permissions, working with the file system, revision control, Unix utilities, environment customization, and using Python for shell scripts. Topics may be added, given sufficient interest. Course website: http://cs1u.stanford.edu
Terms: Aut, Win, Spr | Units: 1 | Grading: Satisfactory/No Credit

CS 20: Tensorflow for Deep Learning Research

This course will cover the fundamentals and contemporary usage of the Tensorflow library for deep learning research. Through the course, students will use Tensorflow to build models of different complexity, from simple linear/logistic regression to convolutional neural network and recurrent neural networks with LSTM to solve tasks such as word embeddings, translation, optical character recognition. Students will also learn best practices to structure a model and manage research experiments. Prerequisites: CS229 or CS224D/N.
Terms: Win | Units: 2 | Grading: Credit/No Credit
Instructors: Manning, C. (PI)

CS 22A: The Social & Economic Impact of Artificial Intelligence

Recent advances in computing may place us at the threshold of a unique turning point in human history. Soon we are likely to entrust management of our environment, economy, security, infrastructure, food production, healthcare, and to a large degree even our personal activities, to artificially intelligent computer systems. The prospect of "turning over the keys" to increasingly autonomous systems raises many complex and troubling questions. How will society respond as versatile robots and machine-learning systems displace an ever-expanding spectrum of blue- and white-collar workers? Will the benefits of this technological revolution be broadly distributed or accrue to a lucky few? How can we ensure that these systems respect our ethical principles when they make decisions at speeds and for rationales that exceed our ability to comprehend? What, if any, legal rights and responsibilities should we grant them? And should we regard them merely as sophisticated tools or as a newly emerging form of life? The goal of CS22 is to equip students with the intellectual tools, ethical foundation, and psychological framework to successfully navigate the coming age of intelligent machines.
Terms: Win | Units: 1 | Grading: Satisfactory/No Credit
Instructors: Kaplan, J. (PI)

CS 51: CS + Social Good Studio: Designing Social Impact Projects

Get real-world experience launching and developing your own social impact projects! Students work in small teams to develop high-impact projects around problem domains provided by partner organizations, under the guidance and support of design/technical coaches from industry and non-profit domain experts. Along with support, resources, and community discussion, the class provides an outlet for students to create social change through CS while providing students with experience engaging in the full product development cycle on real-world projects. Prerequisite: CS 147, equivalent experience, or consent of instructors.
Terms: Win | Units: 2 | Grading: Satisfactory/No Credit

CS 83: Playback Theater For Research

Playback combines elements of theater, community work and storytelling. In a playback show, a group of actors and musicians create an improvised performance based on the audience's personal stories. A playback show brings about a powerful listening and sharing experience. During the course, we will tell, listen, play together, and train in playback techniques. We will write diaries to process our experience in the context of education and research. The course is aimed to strengthen listening abilities, creativity and the collaborative spirit, all integral parts of doing great science. In playback, as in research, we are alwaysnmoving together, from the known, to the unknown, and back.nThere is limited enrollment for this class. Application is required. Apply here: https://docs.google.com/forms/d/1gR4bGkFZh_ycMBGMz1AIIuyv7WyQfX5xTjanGlclK-A/prefill
Terms: Win | Units: 3 | UG Reqs: WAY-CE | Grading: Letter or Credit/No Credit
Instructors: Reingold, O. (PI)

CS 103: Mathematical Foundations of Computing

Mathematical foundations required for computer science, including propositional predicate logic, induction, sets, functions, and relations. Formal language theory, including regular expressions, grammars, finite automata, Turing machines, and NP-completeness. Mathematical rigor, proof techniques, and applications. Prerequisite: CS106B or equivalent. CS106B may be taken concurrently with CS103.
Terms: Aut, Win, Spr | Units: 3-5 | UG Reqs: GER:DB-Math, WAY-FR | Grading: Letter or Credit/No Credit

CS 103A: Mathematical Problem-solving Strategies

Problem solving strategies and techniques in discrete mathematics and computer science. Additional problem solving practice for CS103. In-class participation required. Prerequisite: consent of instructor. Co-requisite: CS103.
Terms: Aut, Win, Spr | Units: 1 | Grading: Satisfactory/No Credit

CS 106A: Programming Methodology (ENGR 70A)

Introduction to the engineering of computer applications emphasizing modern software engineering principles: object-oriented design, decomposition, encapsulation, abstraction, and testing. Emphasis is on good programming style and the built-in facilities of respective languages. No prior programming experience required. Summer quarter enrollment is limited.nnAlternative versions of CS106A are available which cover most of the same material but in different programming languages:nnJava (Fall, Win, Spr, or Sum qtr enroll in CS106A section 1) nJavascript (Fall qtr enroll in CS 106A Section 2)nPython (Winter or Spring qtr enroll in CS 106A Section 3)
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: GER:DB-EngrAppSci, WAY-FR | Grading: Letter or Credit/No Credit

CS 106AP: Programming Methodology in Python

Introduction to the engineering of computer applications in Python, emphasizing modern software engineering principles: decomposition, abstraction, and testing. Emphasis is on good programming style. This course covers most of the same material as CS106A Section 1 in Java and CS 106A Section 2 in JavaScript, but this course uses the Python programming language which is popular for general engineering and web development. Required readings will all be available for free on the web. Students are encouraged to bring a laptop to lecture to do the live exercises which are integrated with lecture. No prior programming experience required. To enroll in this class, enroll in CS 106A Section 3.nnMay be taken for 3 units by grad students.
Terms: Win, Spr | Units: 3-5 | Grading: Letter or Credit/No Credit
Instructors: Parlante, N. (PI)

CS 106B: Programming Abstractions (ENGR 70B)

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. Summer quarter enrollment is limited.
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: GER:DB-EngrAppSci, WAY-FR | Grading: Letter or Credit/No Credit
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