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51 - 60 of 86 results for: CS

CS 247: Human-Computer Interaction Design Studio

Project-based focus on interaction design process, especially early-stage design and rapid prototyping. Methods used in interaction design including needs analysis, user observation, sketching, concept generation, scenario building, and evaluation. Prerequisites: 147 or equivalent background in design thinking; 106B or equivalent background in programming. Recommended: CS 142 or equivalent background in web programming
Terms: Aut, Win | Units: 3-4

CS 249A: Object-Oriented Programming from a Modeling and Simulation Perspective

Topics: large-scale software development approaches for complex applications, class libraries and frameworks; encapsulation, use of inheritance and dynamic dispatch, design of interfaces and interface/implementation separation, exception handling, smart pointers and reference management, minimalizing dependencies and value-oriented programming. Inheritance: when and why multiple inheritance naming, directories, manager, and disciplined use of design patterns including functors, event notification and iterators. Prerequisites: C, C++, and programming methodology as developed in 106B or X, and 107 (107 may be taken concurrently). Recommended: 193D.
Terms: Aut | Units: 3
Instructors: Cheriton, D. (PI)

CS 251: Bitcoin and Crypto Currencies

For advanced undergraduates and for graduate students. The potential applications for Bitcoin-like technologies is enormous. The course will cover the technical aspects of crypto-currencies, blockchain technologies, and distributed consensus. Students will learn how these systems work and how to engineer secure software that interacts with the Bitcoin network and other crypto currencies. Prerequisite: CS110. Recommended: CS255.
Terms: Aut | Units: 3

CS 251P: Bitcoin & Crypto Currencies Lab

Bitcoin has the potential to change how payments are done on the Internet and beyond. In this class, you will build Bitcoin-powered versions of many of the most popular internet services. For example, you will build a search engine that takes in a small amount of bitcoin for each query, a social network that allows individuals to buy internet celebrity endorsements for bitcoin, and a content site that charges a small amount of bitcoin for each page view. In each case, we will show how Bitcoin micropayments can supplant or complement the traditional ad-supported model. The course is based on a weekly hackathon; each Monday you will receive some stub code illustrating the basic mechanics of a Bitcoin-powered internet service, and you will improve this as best you can as an individual or in a small group by the end of Sunday on that week. Winners of each week's hackathon will be recognized. Prerequisites: No previous Bitcoin knowledge is required. Students who have taken CS251 or CS251P will have more context, but this course is all new material. Recommended: Intensive programming experience at the level of CS107 or above.
Terms: Aut, Win | Units: 1 | Repeatable 5 times (up to 5 units total)

CS 265: Randomized Algorithms and Probabilistic Analysis (CME 309)

Randomness pervades the natural processes around us, from the formation of networks, to genetic recombination, to quantum physics. Randomness is also a powerful tool that can be leveraged to create algorithms and data structures which, in many cases, are more efficient and simpler than their deterministic counterparts. This course covers the key tools of probabilistic analysis, and application of these tools to understand the behaviors of random processes and algorithms. Emphasis is on theoretical foundations, though we will apply this theory broadly, discussing applications in machine learning and data analysis, networking, and systems. Topics include tail bounds, the probabilistic method, Markov chains, and martingales, with applications to analyzing random graphs, metric embeddings, random walks, and a host of powerful and elegant randomized algorithms. Prerequisites: CS 161 and STAT 116, or equivalents and instructor consent.
Terms: Aut | Units: 3

CS 273A: A Computational Tour of the Human Genome (BIOMEDIN 273A, DBIO 273A)

Introduction to computational biology through an informatic exploration of the human genome. Topics include: genome sequencing (technologies, assembly, personalized sequencing); functional landscape (genes, gene regulation, repeats, RNA genes, epigenetics); genome evolution (comparative genomics, ultraconservation, co-option). Additional topics may include population genetics, personalized genomics, and ancient DNA. Course includes primers on molecular biology, the UCSC Genome Browser, and text processing languages. Guest lectures from genomic researchers. No prerequisites. See http://cs273a.stanford.edu/.
Terms: Aut | Units: 3

CS 274: Representations and Algorithms for Computational Molecular Biology (BIOE 214, BIOMEDIN 214, GENE 214)

Topics: introduction to bioinformatics and computational biology, algorithms for alignment of biological sequences and structures, computing with strings, phylogenetic tree construction, hidden Markov models, Gibbs Sampling, basic structural computations on proteins, protein structure prediction, protein threading techniques, homology modeling, molecular dynamics and energy minimization, statistical analysis of 3D biological data, integration of data sources, knowledge representation and controlled terminologies for molecular biology, microarray analysis, machine learning (clustering and classification), and natural language text processing. Prerequisites: programming skills; consent of instructor for 3 units.
Terms: Aut | Units: 3-4

CS 279: Computational Biology: Structure and Organization of Biomolecules and Cells (BIOE 279, BIOMEDIN 279, BIOPHYS 279, CME 279)

Computational approaches to understanding the three-dimensional spatial organization of biological systems and how that organization evolves over time. The course will cover cutting-edge research in both physics-based simulations and computational analysis of experimental data, at scales ranging from individual molecules to multiple cells. Prerequisites: elementary programming background (106A or equivalent) and an introductory course in biology or biochemistry.
Terms: Aut | Units: 3

CS 300: Departmental Lecture Series

Priority given to first-year Computer Science Ph.D. students. CS Masters students admitted if space is available. Presentations by members of the department faculty, each describing informally his or her current research interests and views of computer science as a whole.
Terms: Aut | Units: 1
Instructors: Dill, D. (PI)

CS 309A: Cloud Computing

For science, engineering, business, medicine, and law students. Cloud computing is bringing information systems out of the back office and making it core to the entire economy. This class is intended for all students who want to begin to understand the implications of this shift in technology. Guest industry experts are public company CEOs who are delivering application, software development, operations management, compute, storage & data center, and network cloud services.
Terms: Aut | Units: 1 | Repeatable for credit
Instructors: Chou, T. (PI)
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