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1 - 10 of 89 results for: CS ; Currently searching autumn courses. You can expand your search to include all quarters

CS 1C: Introduction to Computing at Stanford

For those with limited experience with computers or who want to learn more about Stanford's computing environment. Topics include: computer maintenance and security, computing resources, Internet privacy, and copyright law. One-hour lecture/demonstration in dormitory clusters prepared and administered weekly by the Resident Computer Consultant (RCC). Final project. Not a programming course.
Terms: Aut | Units: 1 | Grading: Satisfactory/No Credit
Instructors: Smith, S. (PI)

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 7: Personal Finance for Engineers

Introduction to the fundamentals and analysis specifically needed by engineers to make informed and intelligent financial decisions. Course will focus on actual industry-based financial information from technology companies and realistic financial issues. Topics include: behavioral finance, budgeting, debt, compensation, stock options, investing and real estate. No prior finance or economics experience required.
Terms: Aut | Units: 1 | Grading: Satisfactory/No Credit
Instructors: Nash, A. (PI)

CS 9: Problem-Solving for the CS Technical Interview

This course will prepare students to interview for software engineering and related internships and full-time positions in industry. Drawing on multiple sources of actual interview questions, students will learn key problem-solving strategies specific to the technical/coding interview. Students will be encouraged to synthesize information they have learned across different courses in the major. Emphasis will be on the oral and combination written-oral modes of communication common in coding interviews, but which are unfamiliar settings for problem solving for many students. Prerequisites: CS 106B or X.
Terms: Aut | Units: 1 | Grading: Satisfactory/No Credit

CS 28: Artificial Intelligence, Entrepreneurship and Society in the 21stnCentury and Beyond

Technical developments in artificial intelligence (AI) have opened up newnopportunities for entrepreneurship, as well as raised profound longer termnquestions about how human societal and economic systems may benre­organized to accommodate the rise of intelligent machines. In thisncourse, closely co­taught by a Stanford professor and a leading SiliconnValley venture capitalist, we will examine the current state of the artncapabilities of existing artificial intelligence systems, as well asneconomic challenges and opportunities in early stage startups and largencompanies that could leverage AI. We will focus on gaps between businessnneeds and current technical capabilities to identify high impactndirections for the development of future AI technology. Simultaneously, wenwill explore the longer term societal impact of AI driven by inexorablentrends in technology and entrepreneurship. The course includes guestnlectures from leading technologists and entrepreneurs who employ AI in anvariety of fields, including healthcare, education, self­driving cars,ncomputer security, natural language interfaces, computer vision systems,nand hardware acceleration.
Terms: Aut | Units: 2 | Grading: Credit/No Credit
Instructors: Ganguli, S. (PI)

CS 45N: Computers and Photography: From Capture to Sharing

Preference to freshmen with experience in photography and use of computers. Elements of photography, such as lighting, focus, depth of field, aperture, and composition. How a photographer makes photos available for computer viewing, reliably stores them, organizes them, tags them, searches them, and distributes them online. No programming experience required. Digital SLRs and editing software will be provided to those students who do not wish to use their own.
Terms: Aut, Spr | Units: 3-4 | UG Reqs: WAY-CE | Grading: Letter or Credit/No Credit

CS 50: Using Tech for Good

Students in the class will work in small teams to implement high-impact projects for partner organizations. Taught by the CS+Social Good team, the aim of the class is to empower you to leverage technology for social good by inspiring action, facilitating collaboration, and forging pathways towards global change. Recommended: CS 106B, CS 42 or 142. Class is open to students of all years. May be repeated for credit. Cardinal Course certified by the Haas Center.
Terms: Aut, Spr | Units: 2 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: Cain, J. (PI)

CS 53SI: Discussion in Tech for Good

This course introduces students to various intersections of social good and technology through a weekly discussion and speaker series. Students will be given a space to exchange ideas and experiences regarding a certain social issue. Invited speakers come from industry, academia, and non-profit organizations. They will share their career paths, what drove them to these fields, and advice for students. The topics examined will span a broad variety of social issues -- from race and class to education and sustainability -- and help students better understand how to kick off their journey in using computer science for social good.
Terms: Aut | Units: 1 | Grading: Satisfactory/No Credit
Instructors: Sahami, M. (PI)

CS 56N: Great Discoveries and Inventions in Computing

This seminar will explore some of both the great discoveries that underlie computer science and the inventions that have produced the remarkable advances in computing technology. Key questions we will explore include: What is computable? How can information be securely communicated? How do computers fundamentally work? What makes computers fast? Our exploration will look both at the principles behind the discoveries and inventions, as well as the history and the people involved in those events. Some exposure to programming will be helpful, but it not strictly necessary.
Terms: Aut | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: Hennessy, J. (PI)

CS 102: Big Data: Tools and Techniques, Discoveries and Pitfalls

Aimed at non-CS undergraduate and graduate students who want to learn the basics of big data tools and techniques and apply that knowledge in their areas of study. Many of the world's biggest discoveries and decisions in science, technology, business, medicine, politics, and society as a whole, are now being made on the basis of analyzing massive data sets. At the same time, it is surprisingly easy to make errors or come to false conclusions from data analysis alone. This course provides a broad and practical introduction to big data: data analysis techniques including databases, data mining, and machine learning; data analysis tools including spreadsheets, relational databases and SQL, Python, and R; data visualization techniques and tools; pitfalls in data collection and analysis; historical context, privacy, and other ethical issues. Tools and techniques are hands-on but at a cursory level, providing a basis for future exploration and application. Prerequisites: comfort with basic logic and mathematical concepts, along with high school AP computer science, CS106A, or other equivalent programming experience.
Terms: Aut | Units: 3-4 | UG Reqs: WAY-AQR | Grading: Letter or Credit/No Credit
Instructors: Widom, J. (PI)
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