2014-2015 2015-2016 2016-2017 2017-2018 2018-2019
Browse
by subject...
    Schedule
view...
 

121 - 130 of 204 results for: CS

CS 78: Understanding Women's Experience in High-Tech Companies

Women continue to be underrepresented in high-tech companies at every level and companies have problems with retention. In this course students who will form the next generation in these industries will critically look at the lives and challenges of women in technology. They will explore their personal journey, review classic and recent literature on women and work, and conduct field interviews of women in the industry. The students will work in groups to interpret and organize field data to reveal psychosocial, cultural, and organizational themes that affect women's choices. They generate guiding insights for themselves and organizations to be shared with selected groups at Stanford. Required: declared major in computer science or other major with design coursework. Recommended: CS 147 or equivalent experience with design fieldwork.
Terms: Win | Units: 3 | Grading: Letter or Credit/No Credit

CS 93SI: Introduction to Functional Programming in Haskell

A brief introduction to the functional programming paradigm in the Haskell programming language. Recursion, higher-order functions, currying. Lists and list operations. Data types and typeclasses. Functors and Monads.
Terms: Win | Units: 1 | Grading: Satisfactory/No Credit
Instructors: Cooper, S. (PI)

CS 106L: Standard C++ Programming Laboratory

Supplemental lab to 106B and 106X. Additional features of standard C++ programming practice. Possible topics include advanced C++ language features, standard libraries, STL containers and algorithms, object memory management, operator overloading, and inheritance. Prerequisite: consent of instructor. Corequisite: 106B or 106X.
Terms: Aut, Spr | Units: 1 | Grading: Satisfactory/No Credit

CS 109L: Statistical Computing with R Laboratory

Supplemental lab to CS109. Introduces the R programming language for statistical computing. Topics include basic facilities of R including mathematical, graphical, and probability functions, building simulations, introductory data fitting and machine learning. Provides exposure to the functional programming paradigm. Corequisite: CS109.
Terms: Win, Spr | Units: 1 | Grading: Satisfactory/No Credit

CS 154: Introduction to Automata and Complexity Theory

This course provides a mathematical introduction to the following questions: What is computation? Given a computational model, what problems can we hope to solve in principle with this model? Besides those solvable in principle, what problems can we hope to efficiently solve? In many cases we can give completely rigorous answers; in other cases, these questions have become major open problems in computer science and mathematics. By the end of this course, students will be able to classify computational problems in terms of their computational complexity (Is the problem regular? Not regular? Decidable? Recognizable? Neither? Solvable in P? NP-complete? PSPACE-complete?, etc.). Students will gain a deeper appreciation for some of the fundamental issues in computing that are independent of trends of technology, such as the Church-Turing Thesis and the P versus NP problem. Prerequisites: CS 103 or 103B.
Terms: Win | Units: 3-4 | UG Reqs: GER:DB-EngrAppSci | Grading: Letter or Credit/No Credit
Instructors: Williams, R. (PI)

CS 161L: Implementation of Algorithms

Optional companion course to CS 161; provides an opportunity to practice implementing algorithms covered in the lectures and problem sets of CS 161. Students learn implementation details, distinguish practical runtime from asymptotic runtime, and explore the tradeoff between code complexity and runtime complexity. Students are expected to be proficient in either C++ or Java at the 106 level.
Terms: Spr | Units: 1 | Grading: Satisfactory/No Credit
Instructors: Nguyen, A. (PI)

CS 164: Computing with Physical Objects: Algorithms for Shape and Motion

Algorithms and data structures dealing with the representation and manipulation of physical objects and entities in the computer. Computational structures for shape and motion, shape fitting and matching, triangulations and other spatial subdivisions, and low-dimensional search and optimization. Examples relevant to computer graphics, computer vision, robotics and geometric computation emphasizing algorithmic paradigms applicable to multidimensional data. Prerequisites: CS 103 or 103B, and CS 109 or STATS 116, and CS 106B/X or consent of instructor.
Terms: not given this year | Units: 3 | UG Reqs: GER:DB-EngrAppSci | Grading: Letter or Credit/No Credit

CS 173: A Computational Tour of the Human Genome

(Only one of 173 or 273A counts toward any CS degree program.) Introduction to computational biology through an informatic exploration of the human genome. Topics include: genome sequencing; functional landscape of the human genome (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 on current genomic research topics. Class will be similar in spirit to CS273A, which will not be offered this year. Prerequisites: CS107 or equivalent background in programming.
Terms: not given this year | Units: 3 | Grading: Letter or Credit/No Credit

CS 193C: Client-Side Internet Technologies

Client-side technologies used to create web sites such as sophisticated Web 2.0 interfaces similar to Google maps. XHTML, CSS, JavaScript, document object model (DOM), AJAX, and Flash. Prerequisite: programming experience at the level of 106A.
Terms: Sum | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: Young, P. (PI)

CS 196: Computer Consulting

Focus is on Macintosh and Windows operating system maintenance and troubleshooting through hardware and software foundation and concepts. Topics include operating systems, networking, security, troubleshooting methodology with emphasis on Stanford's computing environment. Not a programming course. Prerequisite: 1C or equivalent.
Terms: Win, Spr | Units: 2 | Grading: Satisfactory/No Credit
Instructors: Smith, S. (PI)
Filter Results:
term offered
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