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201 - 210 of 258 results for: CS

CS 371: Computational Biology in Four Dimensions (BIOMEDIN 371, BIOPHYS 371, CME 371)

Cutting-edge research on computational techniques for investigating and designing the three-dimensional structure and dynamics of biomolecules, cells, and everything in between. These techniques, which draw on approaches ranging from physics-based simulation to machine learning, play an increasingly important role in drug discovery, medicine, bioengineering, and molecular biology. Course is devoted primarily to reading, presentation, discussion, and critique of papers describing important recent research developments. Prerequisite: CS 106A or equivalent, and an introductory course in biology or biochemistry. Recommended: some experience in mathematical modeling (does not need to be a formal course).
Terms: not given this year, last offered Winter 2018 | Units: 3 | Grading: Letter or Credit/No Credit

CS 373: Statistical and Machine Learning Methods for Genomics (BIO 268, BIOMEDIN 245, GENE 245, STATS 345)

Introduction to statistical and computational methods for genomics. Sample topics include: expectation maximization, hidden Markov model, Markov chain Monte Carlo, ensemble learning, probabilistic graphical models, kernel methods and other modern machine learning paradigms. Rationales and techniques illustrated with existing implementations used in population genetics, disease association, and functional regulatory genomics studies. Instruction includes lectures and discussion of readings from primary literature. Homework and projects require implementing some of the algorithms and using existing toolkits for analysis of genomic datasets.
Terms: not given this year, last offered Spring 2018 | Units: 3 | Grading: Medical Option (Med-Ltr-CR/NC)

CS 375: Large-Scale Neural Network Modeling for Neuroscience (PSYCH 249)

Introduction to designing, building, and training neural networks for modeling brain and behavioral data, including: deep convolutional neural network models of sensory systems (vision, audition, somatosensation); recurrent neural networks for dynamics, memory and attention; integration of variational and generative methods for cognitive modeling; and methods and metrics for comparing such models to real-world neural data. Attention will be given both to established methods as well as cutting-edge techniques. Students will learn conceptual bases for deep neural network models, and will also implement learn to implement and train large-scale models in Tensorflow using GPUs. Requirements: Fluency in Unix shell and Python programming, familiarity with differential equations, linear algebra, and probability theory, and one or more courses in cognitive or systems neuroscience.
Terms: Aut | Units: 1-3 | Grading: Letter or Credit/No Credit

CS 376: Human-Computer Interaction Research

Prepares students to conduct original HCI research by reading and discussing seminal and cutting-edge research papers. Main topics are ubiquitous computing, social computing, and design and creation; breadth topics include HCI methods, programming, visualization, and user modeling. Student pairs perform a quarter-long research project. Prerequisites: For CS and Symbolic Systems undergraduates/masters students, an A- or better in CS 147 or CS 247. No prerequisite for PhD students or students outside of CS and Symbolic Systems.
Terms: Aut | Units: 3-4 | Repeatable for credit | Grading: Letter (ABCD/NP)

CS 377: Topics in Human-Computer Interaction

Contents change each quarter. May be repeated for credit. See http://hci.stanford.edu/academics for offerings.
Terms: offered occasionally | Units: 2-3 | Repeatable for credit | Grading: Letter or Credit/No Credit

CS 377D: Topics in Learning and Technology: d.compress - Designing Calm (EDUC 328A)

Contents of the course change each year. The course can be repeated. Stress silently but steadily damages physical and emotional well-being, relationships, productivity, and our ability to learn and remember. This highly experiential and project-oriented class will focus on designing interactive technologies to enable calm states of cognition, emotion, and physiology for better human health, learning, creativity and productivity.
Terms: not given this year, last offered Spring 2015 | Units: 3 | Repeatable for credit | Grading: Letter (ABCD/NP)

CS 377E: Designing Solutions to Global Grand Challenges

In this course we creatively apply information technologies to collectively attack Global Grand Challenges (e.g., global warming, rising healthcare costs and declining access, and ensuring quality education for all). Interdisciplinary student teams will carry out need-finding within a target domain, followed by brainstorming to propose a quarter long project. Teams will spend the rest of the quarter applying user-centered design methods to rapidly iterate through design, prototyping, and testing of their solutions. This course will interweave a weekly lecture with a weekly studio session where students apply the techniques hands-on in a small-scale, supportive environment.
Terms: Spr | Units: 3-4 | Grading: Letter (ABCD/NP)
Instructors: Landay, J. (PI)

CS 377G: Designing Serious Games

Over the last few years we have seen the rise of "serious games" to promote understanding of complex social and ecological challenges, and to create passion for solving them. This project-based course provides an introduction to game design principals while applying them to games that teach. Run as a hands-on studio class, students will design and prototype games for social change and civic engagement. We will learn the fundamentals of games design via lecture and extensive reading in order to make effective games to explore issues facing society today. The course culminates in an end-of- quarter open house to showcase our games. Prerequisite: CS147 or equivalent. 247 recommended, but not required.
Terms: Aut, Spr | Units: 3-4 | Grading: Letter or Credit/No Credit

CS 377I: Designing for Complexity

Complex problems require sophisticated approaches. In this project-based hands-on course, students explore the design of systems, information and interface for human use. We will model the flow of interactions, data and context, and crafting a design that is useful, appropriate and robust. Students will create utilities or games as a response to the challenges presented. We will also examine the ethical consequences of design decisions and explore current issues arising from unintended consequences. Prerequisite: CS 147 or equivalent. 247 recommended, but not required. May be repeat for credit
Terms: not given this year | Units: 3-4 | Repeatable for credit | Grading: Letter or Credit/No Credit

CS 377J: Designing Systems for Collaboration, Cooperation, and Collective Action

This project-based class focuses on the design of systems that support large groups to collaborate, cooperate, and act together. A large body of research in Human-Computer Interaction and Computer Supported Cooperative Work is devoted to the design of systems that assist large groups to come together and aggregate their efforts, whether in the form of information, code, or people power. Examples of these sociotechnical systems include Wikipedia, Facebook groups, and Change.org. Students will read papers in the HCI literature and participate in discussions that analyze the design of these systems, the various stakeholders, and how the systems play out in the real world. Prerequisites: CS 147; CS 376 recommended but not required.
Terms: not given this year | Units: 3 | Grading: Letter or Credit/No Credit
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