1 - 10 of 367 results for: CS

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. 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

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.

This course will prepare students to apply and interview for internships and full-time positions in the software engineering industry. Each week, we will have one meeting focused on advice (e.g. resume prep, behavioral interviews, salary negotiation, panel discussions with representatives from startups and big tech), and one meeting focused on working through and discussing one or more coding problems.

Experimental introduction to computer science and electrical engineering. Students will learn to create interactive programs that understand sounds made by real-world musical instruments and the big ideas behind some of the core discoveries, surprises, and impossibilities at the core of CS and EE.

In this hands-on, experiential course, students will design and develop virtual reality applications. You'll learn how to use the Unity game engine, the most popular platform for creating immersive applications. The class will teach the design best practices and the creation pipeline for VR applications. Students will work in groups to present a final project in building an application for the Oculus Quest 2 headset. Enrollment is limited and by application only. See https://cs11si.stanford.edu for more information and the link to the application. Prerequisite: CS 106A or equivalent

This one-unit workshop introduces UX design fundamentals for XR (Extended Reality) applications through a combination of hands-on work sessions and guest lectures from industry and academic experts, focusing on spatial prototyping and introducing Xcode for implementing applications on the Apple Vision Pro. Prerequisite: CS 106A or equivalent basic coding experience. Please go to cs12si.stanford.edu for an application link.

Introduction to version control systems and how they can be used to explore the history of changes in a software project, encourage best practices in the software development process, and aid in collaboration within software engineering teams. Students will learn how to use git to make modular changes in a software repository, explore parallel ideas with branches, merge changes from multiple collaborators, and more. Basic programming at the level of CS 106A is recommended.

Students will explore challenging social issues, and learn about the opportunities and limitations for AI to empower human solutions! You'll learn about applying AI to real-world social good spaces (such as climate, education, and housing) and learn what this looks like in practice. The class provides a high-level overview of the machine learning and deep learning techniques that have already proven effective in tackling social problems. Overall, we aim to center the "social good" component of AI for Social Good and cover material you would not otherwise see in the AI curriculum at Stanford. The course structure alternates between instructional lectures and bi-weekly guest speakers at the forefront of technology for social good. Students will be given the chance to engage in a flexible combination of AI model building, discussion, and individual exploration. Special topics may include: tech ethics, human-centered AI, AI safety, education technology, mental health applications, AI in policy, assistive robotics. Prerequisites: programming experience at the level of CS106A and an interest in social impact! Application required for enrollment: http://tinyurl.com/cs21si2425. We encourage students from all disciplines and backgrounds to apply!

Recent advances in Generative AI are rapidly transforming how we live and work. This lecture course offers a non-technical exploration of its foundational principles, inherent strengths and limitations, and a comprehensive overview of its profound impact on our society and economy. We will delve into critical questions: How will AI reshape labor markets and jobs? What roles will it play in medical research, healthcare, education, entertainment, engineering, transportation, and the legal system? How will it be used - or misused - in democratic societies and autocratic regimes? Will it alter the geopolitical balance of power and the nature of warfare? How can we align these powerful systems with human values? Can machines genuinely create, or possess consciousness? Does the prospect of superintelligence mean the human race is doomed? Will the benefits of this technological revolution be broadly distributed, or accrue to a lucky few? Are we currently experiencing an 'AI bubble'? This course also demystifies essential jargon, such as 'transformers', 'prompt engineering', 'chain of thought', 'hallucination', 'jailbreaking', 'context rot', 'deepfakes', 'stochastic parrots', and 'algorithmic bias'. By equipping students with historical grounding, intellectual tools, ethical frameworks, and psychological perspectives, this course prepares them to thoughtfully navigate the complexities of the AI revolution. (Note: This course is pre-approved for credit at Stanford Law School (SLS) and the Graduate School of Business (GSB). GSB students must enroll in either SYMSYS 122 or INTLPOL 200 for GSB credit. No programming or prior technical knowledge is required.)