2020-2021 2021-2022 2022-2023 2023-2024 2024-2025
Browse
by subject... 		    Schedule
view... 		 

1 - 10 of 19 results for: SYMSYS ; Currently searching autumn courses. You can expand your search to include all quarters

print preview printer friendly page

SYMSYS 1: Minds and Machines (CS 24, LINGUIST 35, PHIL 99, PSYCH 35, SYMSYS 200)

(Formerly SYMSYS 100). An overview of the interdisciplinary study of cognition, information, communication, and language, with an emphasis on foundational issues: What are minds? What is computation? What are rationality and intelligence? Can we predict human behavior? Can computers be truly intelligent? How do people and technology interact, and how might they do so in the future? Lectures focus on how the methods of philosophy, mathematics, empirical research, and computational modeling are used to study minds and machines. Students must take this course before being approved to declare Symbolic Systems as a major. All students interested in studying Symbolic Systems are urged to take this course early in their student careers. The course material and presentation will be at an introductory level, without prerequisites. Note that this is a hybrid course. Students should plan to enroll by the first day of the quarter and check their Stanford email account for instructions on how to access the course material. If you have any questions about the course, please email symsys1staff@gmail.com.
Terms: Aut, Win | Units: 4 | UG Reqs: WAY-FR, GER:DB-SocSci

SYMSYS 8: The Logic Group (Oxford)

If all dogs bark and Fido is a dog, it follows that Fido barks. If Clark Kent owns a car, it follows that Superman owns a car, since Clark Kent is Superman. Yet you might wonder why these statements follow from the said assumptions. Can this perhaps be explained in terms of the statements¿ meanings or their grammatical form? Will the explanation be the same in both cases, or do statements follow from assumptions for a variety of different reasons? Are there laws or principles which conclusively prove the statements from the assumptions? Can these laws be doubted, or are they self-evident?nThe Logic Group will tackle these and similar questions. You will gain a solid understanding of both propositional and predicate logic, including a deductive proof system. You will familiarise yourself with the central concepts of formal reasoning, including syntax and semantics, truth and interpretation, validity and soundness, and the concept of logical consequence. Although formal and technical, the course is accessible to all students, and all may benefit. Studying logic will improve your analytic and critical thinking skills and help you develop a more rigorous and precise writing style. Only open to students residing at Stanford House in Oxford (UK).
Terms: Aut | Units: 1-2

SYMSYS 190: Senior Honors Tutorial

Under the supervision of their faculty honors adviser, students work on their senior honors project. May be repeated for credit.
Terms: Aut, Win, Spr | Units: 1-5 | Repeatable for credit

SYMSYS 191: Senior Honors Seminar

Recommended for seniors doing an honors project. Under the leadership of the Symbolic Systems program coordinator, students discuss, and present their honors project.
Terms: Aut | Units: 1 | Repeatable for credit
Instructors: Davies, T. (PI)

SYMSYS 193: Public Service and Social Impact: Pathways to Purposeful Careers (CSRE 190A, ENGLISH 180, INTNLREL 74, POLISCI 74B, PUBLPOL 75B, SOC 190A, URBANST 190A)

How do I translate my interests and skills into a career in public service and social impact? This course will introduce you to a wide range of roles that help shape public policy and civic life, including government, education, nonprofits, social enterprises, and arts/media. It can be taken for one or two units. For one unit, you participate in a weekly, interactive speaker series designed to give you a sense for what different public service careers are like. Each week, guests describe their organizations and roles, highlight key intellectual issues and policy challenges, discuss their career paths, and describe skills crucial for the job. For a second unit, you participate in a hands-on weekly session designed to help you translate this knowledge into action. You will identify roles and organizations that might be a good match for you, build your network through informational interviewing, receive career coaching, and acquire the tools you need to launch your job or internship searc more »
How do I translate my interests and skills into a career in public service and social impact? This course will introduce you to a wide range of roles that help shape public policy and civic life, including government, education, nonprofits, social enterprises, and arts/media. It can be taken for one or two units. For one unit, you participate in a weekly, interactive speaker series designed to give you a sense for what different public service careers are like. Each week, guests describe their organizations and roles, highlight key intellectual issues and policy challenges, discuss their career paths, and describe skills crucial for the job. For a second unit, you participate in a hands-on weekly session designed to help you translate this knowledge into action. You will identify roles and organizations that might be a good match for you, build your network through informational interviewing, receive career coaching, and acquire the tools you need to launch your job or internship search. This course is intended for all students and all majors. Course content will be relevant to students soon entering the job market as well as those facing choices about courses of study and internships. Class sessions will be 60 minutes. This course is co-sponsored by the Haas Center for Public Service, the School of Humanities and Sciences, and Stanford in Government. Students taking the course for one unit (Tuesday lecture) must enroll in the -01 course option, and students taking the course for two units (Tuesday lecture and Thursday seminar) must enroll in the -02 course option. IR approved.
Terms: Aut | Units: 2
Instructors: Sims, J. (PI) ; Weisler, T. (PI) ; Flores, E. (TA)

SYMSYS 195A: Design for Artificial Intelligence (CS 247A)

A project-based course that builds on the introduction to design in CS147 by focusing on advanced methods and tools for research, prototyping, and user interface design. Studio based format with intensive coaching and iteration to prepare students for tackling real world design problems. This course takes place entirely in studios; you must plan on attending every studio to take this class. The focus of CS247A is design for human-centered artificial intelligence experiences. What does it mean to design for AI? What is HAI? How do you create responsible, ethical, human centered experiences? Let us explore what AI actually is and the constraints, opportunities and specialized processes necessary to create AI systems that work effectively for the humans involved. Prerequisites: CS147 or equivalent background in design thinking. In the event of a waitlist, acceptance to class based on an application provided on the first day of class.
Terms: Aut, Spr | Units: 3-4
Instructors: Stanford, J. (PI)

SYMSYS 195I: Image Systems Engineering (PSYCH 221)

This course is an introduction to digital imaging technologies. We focus on the principles of key elements of digital systems components; we show how to use simulation to predict how these components will work together in a complete image system simulation. The early lectures introduce the software environment and describe options for the course project. The following topics are covered and software tools are introduced:n- Basic principles of optics (Snell's Law, diffraction, adaptive optics).n- Image sensor and pixel designsn- Color science, metrics, and calibrationn- Human spatial resolutionn- Image processing principlesn- Display technologiesnA special theme of this course is that it explains how imaging technologies accommodate the requirements of the human visual system. The course also explains how image systems simulations can be useful in neuroscience and industrial vision applications. The course consists of lectures, software tutorials, and a course project. Tutorials and projects include extensive software simulations of the imaging pipeline. Some background in mathematics (linear algebra) and programming (Matlab) is valuable.nPre-requisite: EE 261 or equivalent. Or permission of instructor required.
Terms: Aut | Units: 1-3
Instructors: Wandell, B. (PI)

SYMSYS 195M: Measuring Learning in the Brain (EDUC 464, NEPR 464, PSYCH 279)

Everything we learn - be it a historical fact, the meaning of a new word, or a skill like reading, math, programming or playing the piano - depends on brain plasticity. The human brain's incredible capacity for learning is served by a variety of learning mechanisms that all result in changes in brain structure and function over different time scales. The goal of this course is to (a) provide an overview of different learning systems in the brain, (b) introduce methodologies and experiments that have led to new discoveries linking human brain plasticity and learning, (3) design an experiment, collect neuroimaging data, and measure the neurobiological underpinnings of learning in your own brain with MRI. The first section of the course will involve a series of lectures and discussions on the foundations of plasticity and learning with particular attention to experimental methods used in human neuroimaging studies. The second part of the course will involve workshops on designing and impl more »
Everything we learn - be it a historical fact, the meaning of a new word, or a skill like reading, math, programming or playing the piano - depends on brain plasticity. The human brain's incredible capacity for learning is served by a variety of learning mechanisms that all result in changes in brain structure and function over different time scales. The goal of this course is to (a) provide an overview of different learning systems in the brain, (b) introduce methodologies and experiments that have led to new discoveries linking human brain plasticity and learning, (3) design an experiment, collect neuroimaging data, and measure the neurobiological underpinnings of learning in your own brain with MRI. The first section of the course will involve a series of lectures and discussions on the foundations of plasticity and learning with particular attention to experimental methods used in human neuroimaging studies. The second part of the course will involve workshops on designing and implementing experiments in MATLAB/Psychtoolbox or Python/PsychoPy. During this part of the course students will design, present and implement their own experiments as group projects. Finally, students will learn how to collect and analyze MRI data by being participants in their own fMRI experiments or analyzing publicly available datasets. Requirements: This class is designed for students who are interested in gaining hands-on experience with measuring the neurobiological underpinnings of learning. Student projects will involve designing experiments, collecting and analyzing data. So some experience with MATLAB/Python or an equivalent programming language is required. Some background in neuroscience (at least 1 course) is also required as we will assume basic knowledge.
Terms: Aut | Units: 3
Instructors: Yeatman, J. (PI)

SYMSYS 195Q: What does AI get right and wrong about language?

Do you really trust AI to understand your words and intentions? In this course, we will challenge the hype surrounding AI language processing and dive into what it truly gets right and wrong about language. You will learn not only about the staggering achievements of AI language models, but also about the limitations and biases that threaten their reliability. Through hands-on exercises and real-world case studies, you will explore how AI can struggle with understanding complex sentence structures, cultural nuances, and even basic language usage. You will also examine the ethical implications of relying on AI for language processing, including the potential for perpetuating existing biases and discrimination in society. This course will equip you with the critical thinking skills needed to navigate the complex and rapidly evolving world of AI language technology. Prior experience with linguistics and/or artificial intelligence is encouraged but not required.
Terms: Aut | Units: 3
Instructors: Ziegler, J. (PI)

SYMSYS 196: Independent Study

Independent work under the supervision of a faculty member. Can be repeated for credit.
Terms: Aut, Win, Spr | Units: 1-15 | Repeatable for credit
Filter Results:
term offered
updating results...
teaching presence
updating results...
number of units
updating results...
time offered
updating results...
days
updating results...
UG Requirements (GERs)
updating results...
component
updating results...
career
updating results...
© Stanford University | Terms of Use | Copyright Complaints