Computer Science Stanford University. Courses. CS 1. C. Latihan Soal Uts Matematika Kelas 1 Sd Semester 1.

Introduction to Computing at Stanford. Unit. For those with limited experience with computers or who want to learn more about Stanford's computing environment.

Topics include: computer maintenance and security, computing resources, Internet privacy, and copyright law. One- hour lecture/demonstration in dormitory clusters prepared and administered weekly by the Resident Computer Consultant (RCC). Final project. Not a programming course.

CS 1. U. Practical Unix. Unit. 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. The time listed on AXESS is for the first week's logistical meeting only. 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: //cs. CS 7. Personal Finance for Engineers. Unit. 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. CS 9. Problem- Solving for the CS Technical Interview. Unit. This course will prepare students to interview for software engineering and related internships and full- time positions in industry.

Drawing on multiple sources of actual interview questions, students will learn key problem- solving strategies specific to the technical/coding interview. Students will be encouraged to synthesize information they have learned across different courses in the major. Emphasis will be on the oral and combination written- oral modes of communication common in coding interviews, but which are unfamiliar settings for problem solving for many students. Prerequisites: CS 1. B or X. CS 2. 0. Tensorflow for Deep Learning Research. Units. This course will cover the fundamentals and contemporary usage of the Tensorflow library for deep learning research. Through the course, students will use Tensorflow to build models of different complexity, from simple linear/logistic regression to convolutional neural network and recurrent neural networks with LSTM to solve tasks such as word embeddings, translation, optical character recognition.

Students will also learn best practices to structure a model and manage research experiments. Prerequisites: CS2. CS2. 24. D/N. CS 2. A. The Social & Economic Impact of Artificial Intelligence. Unit. Recent advances in computing may place us at the threshold of a unique turning point in human history.

CHAPTER 11 GALILEO: A SIMULATION TOOL FOR LEO SATELLITE CONSTELLATIONS· Laurent Franck and Francesco Potorti ABSTRACT We present Galileo, a simulator for the. By Pieter Hintjens, CEO of iMatix. Please use the issue tracker for all comments and errata. This version covers the latest stable release of ZeroMQ (3.2). SkillSoft - US English IT Skills Course Catalog (Includes Project Management Courses) NOTE: Click on a Solution Area link below to go to that Solution Area. IEEE Projects Trichy, Best IEEE Project Centre Chennai, Final Year Projects in Trichy - We Provide IEEE projects 2016 - 2017, IEEE 2016 Java Projects for M.E/M.Tech.

Soon we are likely to entrust management of our environment, economy, security, infrastructure, food production, healthcare, and to a large degree even our personal activities, to artificially intelligent computer systems. The prospect of "turning over the keys" to increasingly autonomous systems raises many complex and troubling questions.

How will society respond as versatile robots and machine- learning systems displace an ever- expanding spectrum of blue- and white- collar workers? Will the benefits of this technological revolution be broadly distributed or accrue to a lucky few? How can we ensure that these systems respect our ethical principles when they make decisions at speeds and for rationales that exceed our ability to comprehend? What, if any, legal rights and responsibilities should we grant them?

And should we regard them merely as sophisticated tools or as a newly emerging form of life? The goal of CS2. 2 is to equip students with the intellectual tools, ethical foundation, and psychological framework to successfully navigate the coming age of intelligent machines. CS 2. 8. Artificial Intelligence, Entrepreneurship and Society in the 2. Century and Beyond.

Units. Technical developments in artificial intelligence (AI) have opened up new opportunities for entrepreneurship, as well as raised profound longer term questions about how human societal and economic systems may be re­organized to accommodate the rise of intelligent machines. In this course, closely co­taught by a Stanford professor and a leading Silicon Valley venture capitalist, we will examine the current state of the art capabilities of existing artificial intelligence systems, as well as economic challenges and opportunities in early stage startups and large companies that could leverage AI. We will focus on gaps between business needs and current technical capabilities to identify high impact directions for the development of future AI technology. Simultaneously, we will explore the longer term societal impact of AI driven by inexorable trends in technology and entrepreneurship. The course includes guest lectures from leading technologists and entrepreneurs who employ AI in a variety of fields, including healthcare, education, self­driving cars, computer security, natural language interfaces, computer vision systems, and hardware acceleration. CS 4. 1. Hap. py Code: The Python Programming Language.

Units. The fundamentals and contemporary usage of the Python programming language. Primary focus on developing best practices in writing Python and exploring the extensible and unique parts of Python that make it such a powerful language.

Topics include: data structures (e. We will also cover object- oriented design, the standard library, and common third- party packages (e. Time permitting, we will explore modern Python- based web frameworks and project distribution. Prerequisite: 1. 06. B/X or equivalent.

Best CCNA training in Noida delivered by Sky Infotech with live-projects training. The best CCNA training institute in Noida with 100% placement assistance. Call. BGP - The Border Gateway Protocol / Advanced Internet Routing. Complete Technical Acronyms, Glossary & Definitions for PC, SAN, NAS, QA, Testing, HDTV, Wireless, Linux, Embedded, Networks, Video, Digital, pharma, Unix, Video.

Application required. CS 4. 2. Callback Me Maybe: Contemporary Javascript. Units. Introduction to the Java. Script programming language with a focus on building contemporary applications. Course consists of in- class activities and programming assignments that challenge students to create functional web apps (e. Yelp, Piazza, Instagram). Topics include syntax/semantics, event- based programming, document object model (DOM), application programming interfaces (APIs), asynchronous Java.

Compendium of all course descriptions for courses available at Reynolds Community College. Note: The terms in which a course is normally taught is at the end of each description (F=Fall, Sp=Spring, Su=Summer). Jump to TN eCampus Courses. A list of eleven open-source network simulators that run on Linux or FreeBSD systems, and use open-source router software.

Script and XML (AJAX), j. Query, Node. js, and Mongo. DB. Prerequisite: CS 1. CS 4. 5N. Computers and Photography: From Capture to Sharing. Units. Preference to freshmen with experience in photography and use of computers.

Elements of photography, such as lighting, focus, depth of field, aperture, and composition. How a photographer makes photos available for computer viewing, reliably stores them, organizes them, tags them, searches them, and distributes them online. No programming experience required.

Digital SLRs and editing software will be provided to those students who do not wish to use their own. CS 4. 9N. Using Bits to Control Atoms. Units. This is a crash course in how to use a stripped- down computer system aboutnthe size of a credit card (the rasberry pi computer) to control as manyndifferent sensors as we can implement in ten weeks, including LEDs, motionnsensors, light controllers, and accelerometers. The ability to fearlesslyngrab a set of hardware devices, examine the data sheet to see how to usenit, and stitch them together using simple code is a secret weapon thatnsoftware- only people lack, and allows you to build many interestingngadgets. We will start with a ``bare metal'' system - -- no operatingnsystem, no support - -- and teach you how to read device data sheetsndescribing sensors and write the minimal code needed to control themn(including how to debug when things go wrong, as they always do).

MQ - The Guide - ØMQBy Pieter Hintjens, CEO of i. Matix. Please use the issue tracker for all comments and errata.

This version covers the latest stable release of Zero. MQ (3. 2). If you are using older versions of Zero. MQ then some of the examples and explanations won't be accurate. The Guide is originally in C, but also in PHP, Python, Lua, and Haxe.

We've also translated most of the examples into C++, C#, CL, Delphi, Erlang, F#, Felix, Haskell, Java, Objective- C, Ruby, Ada, Basic, Clojure, Go, Haxe, Node. Perl, and Scala. Zero. MQ (also known as ØMQ, 0. MQ, or zmq) looks like an embeddable networking library but acts like a concurrency framework. It gives you sockets that carry atomic messages across various transports like in- process, inter- process, TCP, and multicast. You can connect sockets N- to- N with patterns like fan- out, pub- sub, task distribution, and request- reply. It's fast enough to be the fabric for clustered products.

Its asynchronous I/O model gives you scalable multicore applications, built as asynchronous message- processing tasks. It has a score of language APIs and runs on most operating systems.

Zero. MQ is from i. Matix and is LGPLv. We took a normal TCP socket, injected it with a mix of radioactive isotopes stolen from a secret Soviet atomic research project, bombarded it with 1. Yes, Zero. MQ sockets are the world- saving superheroes of the networking world. Figure 1 - A terrible accident…The Ø in Zero. MQ is all about tradeoffs.

On the one hand this strange name lowers Zero. MQ's visibility on Google and Twitter. On the other hand it annoys the heck out of some Danish folk who write us things like "ØMG røtfl", and "Ø is not a funny looking zero!" and "Rødgrød med fløde!", which is apparently an insult that means "may your neighbours be the direct descendants of Grendel!" Seems like a fair trade. Originally the zero in Zero.

MQ was meant as "zero broker" and (as close to) "zero latency" (as possible). Since then, it has come to encompass different goals: zero administration, zero cost, zero waste. More generally, "zero" refers to the culture of minimalism that permeates the project. We add power by removing complexity rather than by exposing new functionality.

This book is written for professional programmers who want to learn how to make the massively distributed software that will dominate the future of computing. We assume you can read C code, because most of the examples here are in C even though Zero.

MQ is used in many languages. We assume you care about scale, because Zero. MQ solves that problem above all others. We assume you need the best possible results with the least possible cost, because otherwise you won't appreciate the trade- offs that Zero. MQ makes. Other than that basic background, we try to present all the concepts in networking and distributed computing you will need to use Zero.

MQ. Thanks to Andy Oram for making the O'Reilly book happen, and editing this text. Thanks to Bill Desmarais, Brian Dorsey, Daniel Lin, Eric Desgranges, Gonzalo Diethelm, Guido Goldstein, Hunter Ford, Kamil Shakirov, Martin Sustrik, Mike Castleman, Naveen Chawla, Nicola Peduzzi, Oliver Smith, Olivier Chamoux, Peter Alexander, Pierre Rouleau, Randy Dryburgh, John Unwin, Alex Thomas, Mihail Minkov, Jeremy Avnet, Michael Compton, Kamil Kisiel, Mark Kharitonov, Guillaume Aubert, Ian Barber, Mike Sheridan, Faruk Akgul, Oleg Sidorov, Lev Givon, Allister Mac. Leod, Alexander D'Archangel, Andreas Hoelzlwimmer, Han Holl, Robert G. Jakabosky, Felipe Cruz, Marcus Mc. Curdy, Mikhail Kulemin, Dr.

Gergő Érdi, Pavel Zhukov, Alexander Else, Giovanni Ruggiero, Rick "Technoweenie", Daniel Lundin, Dave Hoover, Simon Jefford, Benjamin Peterson, Justin Case, Devon Weller, Richard Smith, Alexander Morland, Wadim Grasza, Michael Jakl, Uwe Dauernheim, Sebastian Nowicki, Simone Deponti, Aaron Raddon, Dan Colish, Markus Schirp, Benoit Larroque, Jonathan Palardy, Isaiah Peng, Arkadiusz Orzechowski, Umut Aydin, Matthew Horsfall, Jeremy W. Sherman, Eric Pugh, Tyler Sellon, John E. Vincent, Pavel Mitin, Min RK, Igor Wiedler, Olof Åkesson, Patrick Lucas, Heow Goodman, Senthil Palanisami, John Gallagher, Tomas Roos, Stephen Mc. Quay, Erik Allik, Arnaud Cogoluègnes, Rob Gagnon, Dan Williams, Edward Smith, James Tucker, Kristian Kristensen, Vadim Shalts, Martin Trojer, Tom van Leeuwen, Hiten Pandya, Harm Aarts, Marc Harter, Iskren Ivov Chernev, Jay Han, Sonia Hamilton, Nathan Stocks, Naveen Palli, and Zed Shaw for their contributions to this work. How to explain Zero.

MQ? Some of us start by saying all the wonderful things it does. It's sockets on steroids. It's like mailboxes with routing. It's fast! Others try to share their moment of enlightenment, that zap- pow- kaboom satori paradigm- shift moment when it all became obvious. Things just become simpler. Complexity goes away. It opens the mind.

Others try to explain by comparison. It's smaller, simpler, but still looks familiar. Personally, I like to remember why we made Zero. MQ at all, because that's most likely where you, the reader, still are today. Programming is science dressed up as art because most of us don't understand the physics of software and it's rarely, if ever, taught. The physics of software is not algorithms, data structures, languages and abstractions.

These are just tools we make, use, throw away. The real physics of software is the physics of people—specifically, our limitations when it comes to complexity, and our desire to work together to solve large problems in pieces. This is the science of programming: make building blocks that people can understand and use easily, and people will work together to solve the very largest problems.

We live in a connected world, and modern software has to navigate this world. So the building blocks for tomorrow's very largest solutions are connected and massively parallel.

It's not enough for code to be "strong and silent" any more. Code has to talk to code. Code has to be chatty, sociable, well- connected. Code has to run like the human brain, trillions of individual neurons firing off messages to each other, a massively parallel network with no central control, no single point of failure, yet able to solve immensely difficult problems. And it's no accident that the future of code looks like the human brain, because the endpoints of every network are, at some level, human brains. If you've done any work with threads, protocols, or networks, you'll realize this is pretty much impossible.

It's a dream. Even connecting a few programs across a few sockets is plain nasty when you start to handle real life situations. Trillions? The cost would be unimaginable.

Connecting computers is so difficult that software and services to do this is a multi- billion dollar business. So we live in a world where the wiring is years ahead of our ability to use it.

We had a software crisis in the 1. Fred Brooks believed there was no "Silver Bullet" to "promise even one order of magnitude of improvement in productivity, reliability, or simplicity".

Brooks missed free and open source software, which solved that crisis, enabling us to share knowledge efficiently. Today we face another software crisis, but it's one we don't talk about much. Only the largest, richest firms can afford to create connected applications. There is a cloud, but it's proprietary. Our data and our knowledge is disappearing from our personal computers into clouds that we cannot access and with which we cannot compete.

Who owns our social networks? It is like the mainframe- PC revolution in reverse. We can leave the political philosophy for another book. The point is that while the Internet offers the potential of massively connected code, the reality is that this is out of reach for most of us, and so large interesting problems (in health, education, economics, transport, and so on) remain unsolved because there is no way to connect the code, and thus no way to connect the brains that could work together to solve these problems.