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Computer Science 143 - CS

Course Description . The goal of CS143 is to introduce students to relational database systems (RDB) and teach them how they work and how to use them for applications. Through the class, students will learn the RDB model and the SQL language. SQL is the standard language for the creation, query and modification of relational databases.

Actived: Tuesday Apr 13, 2021

Detail: http://web.cs.ucla.edu/classes/fall14/cs143/

UCLA Computer Science M51A Syllabus

Posted: (0 seconds ago) CS m51A, same as Electrical Engineering m16, is a 4-unit course with four hours of lecture and two hours of discussion per week. Topics covered include: introduction to digital systems, specification and implementation of combinational and sequential systems, standard logic modules and programmable logic arrays, specification and implementation of algorithmic systems: data and control sections, number systems and arithmetic algorithms.

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UCLA Computer Science M51A Syllabus

Posted: (0 seconds ago) CS m51A, same as Electrical Engineering m16, is a 4-unit course with four hours of lecture and two hours of discussion per week. Topics covered include: introduction to digital systems, specification and implementation of combinational and sequential systems, standard logic modules and programmable logic arrays, specification and implementation ...

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CS | Computer Science

Posted: (0 seconds ago) Apr 09, 2021  · Computer science is a branch of engineering that encompasses the design, modeling, analysis, and applications of computer systems. Its study at UCLA provides education at the undergraduate and graduate levels necessary to understand, design, implement, and use the software and hardware of digital computers and digital systems.

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Chapter 2: Entity-Relationship Model - CS | Computer Science

Posted: (0 seconds ago) The discriminator of course-offering would be semester (including year) and section-number (if there is more than one section) If we model course-offering as a strong entity we would model course-number as an attribute. Then the relationship with course would be implicit in the course-number attribute

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CS118: Computer Network Fundamentals

Posted: (0 seconds ago) The course will begin with an overview of networking concepts (Chapter 1) and then cover Network Application Protocols (Chapter 2) such as web (http) and email (smtp). Of particular interest in Chapter 2 is the Domain Name System (DNS) and the DNS will be the focus of a course project.

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Course - University of California, Los Angeles

Posted: (0 seconds ago) The course grades reflect team results, initiative and work quality; and individual participation. Calendar: Project - 1 st 3 Weeks: Form team. Choose project. Project teams of three or four members. Merge different visions of what will be done. Teams can work on coordinated projects, or …

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Undergraduate Requirements | CS

Posted: (0 seconds ago) Students can access the CS course homepages maintained by the course instructor and the teaching assistant. Admissions. All applicants to the UCLA Computer Science Department Undergraduate Program must apply through the Office of Academic and Student Affairs in the Henry Samueli School of Engineering and Applied Science (HSSEAS).

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UCLA Computer Science 33 Syllabus

Posted: (0 seconds ago) Course Description CS 33, is a 4-unit course with four hours of lecture and two hours of discussion per week. Topics covered include: information representation and manipulation, floating-point representation, machine level representation of programs, code generation, code …

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CS 239: Big Data Systems - CS | Computer Science

Posted: (0 seconds ago) Course Overview Modern computing has entered the era of big data. This class will introduce the concepts and state-of-the-art in modern big data systems. Specifically, we will cover these topics: _ Key challenges in big data processing _ Storage systems: HDFS, GFS, Big …

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CM146: Introduction to Machine Learning (Winter 2019)

Posted: (0 seconds ago) Course description. Machine Learning encompasses the study of algorithms that learn from data. It has been a key component in a number of problem domains including computer vision, natural language processing, computational biology and robotics.

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Undergrad Student Enrollment in Undergraduate Computer ...

Posted: (0 seconds ago) If the course you are interested in is CS 32 (in a quarter in which it is offered), then instead of using the Enrollment Consideration Request Form, use the CS 32 form. Don't waste a first pass enrollment opportunity on CS 32 (unless it's for Winter quarter and you really want the 10:00 section). Requisites for CS courses are enforced.

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Graduate Student Handbook | CS

Posted: (0 seconds ago) However, courses, course descriptions, instructor designations, curricular degree requirements, and fees described herein are subject to change or deletion without notice. In all matters, the rules and regulations of the UCLA General Catalog and the Standards and Procedures for Graduate Study at UCLA shall supersede this handbook.

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CS 111 Course Reference

Posted: (0 seconds ago) Most of the readings for this course will come from Remzi Arpaci-Dusseau 's Operating Systems in Three Easy Pieces.This is an online textbook, so you will not need to purchase a book for this class. However, the course covers certain topics that are not discussed in this textbook.

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UCLA Samueli Launches New Computer Science Summer ...

Posted: (0 seconds ago) Feb 24, 2021  · To complete the course, students will work on a advisor-supervised capstone project — a fun assignment requiring application of techniques learned throughout the course. In order to create a more diverse and inclusive cohort for this program, full and partial need-based scholarships will be provided to 5-10% of participants.

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Teaching · Tony Nowatzki - CS

Posted: (0 seconds ago) This course is designed to demystify computer systems, covering the basics of computer architecture, computer organization, operating systems and concurrency. First we build from the bottom up with detailed explanations of number systems, how they are employed in the instruction set architecture.

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CS 145: Introduction to Data Mining - CS | Computer Science

Posted: (0 seconds ago) Description: This course introduces basic concepts, algorithms, and techniques of data mining on different types of datasets, including (1) vector data, (2) set data, (3) sequence data, and (4) text data. The class project involves hands-on practice of mining useful knowledge from large data sets. The course is an undergraduate-level computer science course. Also, the course may attract students from other disciplines who need to understand, develop, and use data mining techniques to analyze large amount…

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CS143: Introduction

Posted: (0 seconds ago) Course Objective. Learn how to use database systems. Learn data model. Learn SQL (Structured Query Language) Learn Relational Database Management Systems (RDBMS) Learn basics of other non-relational DBMS (NoSQL) By the end of the quarter you will know. How to store data in DBMS. How to retrieve and interact with data in RDBMS using SQL

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Graduate Admissions | CS

Posted: (0 seconds ago) Dec 01, 2020  · *Computer Science Graduate Admissions Changes Due to COVID-19* **GRE Requirement for Fall 2021-2022 Admissions Cycle Only** Students who wish to apply for admission to our graduate program for the 2021-2022 academic year (applications for this cycle are due December 1, 2020) are not required to take the GRE or submit a GRE score report as part of their application …

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Syllabus - CS118: Computer Network Fundamentals - Spring ...

Posted: (0 seconds ago) Basic Course Information This course provides an introduction to fundamental concepts in the design and implementation of computer communication networks, their protocols, and applications. Topics to be covered include: layered network architecture, physical layer and data link protocols, network and transport protocols, unicast and multicast ...

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Winter 2021 CS 32

Posted: (0 seconds ago) The Winter 2021 CS 32 website is no longer accessible. Academic Integrity. Project 3 spec & FAQ. Project 4 spec

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Syllabus - CS118: Computer Network Fundamentals - Fall ...

Posted: (0 seconds ago) Basic Course Information This course provides an introduction to fundamental concepts in the design and implementation of computer communication networks, their protocols, and applications. Topics to be covered include: layered network architecture, physical layer and data link protocols, network and transport protocols, unicast and multicast ...

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CS260 ML Algorithms - University of California, Los Angeles

Posted: (0 seconds ago) The course will consist of biweekly lectures, problem sets that contain both mathemetical and MATLAB/Octave programming exercises, and two in-class exams. Prerequisites. Undergraduate level training or coursework in algorithms, linear algebra, calculus and multivariate calculus, basic probability and statistics; an undergraduate level course in ...

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CS 145: Introduction to Data Mining - CS | Computer Science

Posted: (0 seconds ago) Class Schedule. CS 145: Introduction to Data Mining News [10/2/2017] First day of class. [10/1/2017] Book refers to: Jiawei Han, Micheline Kamber, and Jian …

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Causal Analysis in Theory and Practice

Posted: (0 seconds ago) Jan 01, 2000  · This, of course, is the exact opposite of what we have been hearing in the news media. (For example, Graeme Wood in The Atlantic: “Black people die of COVID-19 at a higher rate than white people do.”) Have we been victimized by a media deception? The answer is NO, but the explanation underscores the importance of understanding the causal ...

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Causal Analysis in Theory and Practice » Bad Control

Posted: (0 seconds ago) Aug 14, 2019  · Carlos Cinelli, Andrew Forney and Judea Pearl. Update: check the updated and extended version of the crash course here. Introduction. If you were trained in traditional regression pedagogy, chances are that you have heard about the problem of “bad controls”.

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CM146: Introduction to Machine Learning (Fall 2017)

Posted: (0 seconds ago) Course description. Machine Learning encompasses the study of algorithms that learn from data. It has been a key component in a number of problem domains including computer vision, natural language processing, computational biology and robotics.

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CS188: Introduction to Machine Learning (Winter 2017)

Posted: (0 seconds ago) Course description. Machine Learning encompasses the study of algorithms that learn from data. It has been a key component in a number of problem domains including computer vision, natural language processing, computational biology and robotics.

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CS M226 / BIOINF M226/ HUMGEN M226: Machine Learning for ...

Posted: (0 seconds ago) Course format. Homework (50%): There will be periodic homeworks. Questions on the homework will include programming exercises and data analyses. We will use gradescope to manage submission of homeworks. Homeworks are due at 11:59pm on the due date. Late submissions will not be accepted

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Computer Science 143 - CS

Posted: (0 seconds ago) Course Description . The goal of CS143 is to introduce students to relational database systems (RDB) and teach them how to use them for applications. Through the class, students will learn the RDB model and the SQL language. SQL is the standard language for the creation, query and modification of relational databases.

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COM SCIM229S-2 / BIOL CHM229S-2 / HUM GENM229S-2: …

Posted: (0 seconds ago) The course aims to introduce CS/Statistics students to an important set of problems and Bioinformatics/Human Genetics students to a rich set of tools. Prerequisites. Familiarity with probability, statistics, linear algebra and algorithms is expected. No familiarity with biology is needed.

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cs161 Syllabus - web.cs.ucla.edu

Posted: (0 seconds ago) This is an undergraduate course that introduces the fundamental problem solving and knowledge representation paradigms of artificial intelligence. The first couple lectures review the LISP programming language. The next part of the course will cover problem solving including problem spaces, brute-force and heuristic search, two-player games ...

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CompSci 142 / CSE 142 Spring 2014, Course Reference

Posted: (0 seconds ago) Your course grade will be determined from the weighted combination of your scores on each of six projects, one Midterm, and one Final Exam. The weights of each of these are: Six projects, 40% ; Midterm, 30%; Final Exam, 30%; Determining final grades. Course grades will be curved. My grading policy is as follows:

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CS M226 / BIOINF M226/ HUMGEN M226: Machine Learning for ...

Posted: (0 seconds ago) Course format. Homework: There will be five homeworks. Questions on the homework will include programming exercises and data analyses. You can are strongly encouraged to use R (R is free software. See here for details ). The homeworks must be submitted in hard copy in class on the day they are due. Late submissions will not be accepted.

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Frame Page - CS

Posted: (0 seconds ago) B. One-Semester course: All chapters and a choice of problem sets from the WWW site for hands-on experience. In the case of a course with laboratory, only Chapters 1 through 11. C. One-Quarter/Semester Elective course: Follows A or B. It also covers Chapters 12 through 15, and VHDL sections in all chapters.

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CS 31 Summer 2014 Syllabus

Posted: (0 seconds ago) The official course textbook is Absolute C++, Fifth Edition, by Walter Savitch, Addison Wesley, 2013. There are other books on C++ available online for free which are suitable for this course and could well be used as a replacement for the official course textbook.

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Teaching - University of California, Los Angeles

Posted: (0 seconds ago) This combined undergraduate and graduate capstone course (M186 concurrently scheduled with course M286, in three departments) is normally offered in Fall Quarter only and includes two hours of lecture and a two hour simulation laboratory – for five credit units. An introductory course in signals and systems (e.g. EE 102) is co- or prerequisite. The course content covers the “how-to” and ...

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CompSci 142 / CSE 142 Spring 2014, Lab Manual

Posted: (0 seconds ago) Submitting your assignments. When you complete each project, you must submit it to us electronically. For each project, you will find an assignment dropbox in the EEE course website. Please name your submission last_first_projectx.zip, where last and first are your last and first name, and x …

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Network Verification and the Creative Habit

Posted: (0 seconds ago) In this reading course, we will divide the world into 3 parts. Recognizing that networks have a data plane (e.g., IP forwarding) and a control plane (that builds the forwarding plane, e.g., BGP) we will study key papers in: data plane verification (Anteater, Veriflow, HSA, NetPlumber, Atomic Predicates, NoD, and the use of symmetries for ...

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Guy Van den Broeck - CS 161 - Fundamentals of Artificial ...

Posted: (0 seconds ago) This course studies the design of intelligent agents. It introduces the fundamental problem-solving and knowledge-representation paradigms of artificial intelligence. We will study the AI programming language LISP, state-space and problem reduction methods, brute-force and heuristic search, planning techniques, two-player games, and recent ...

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CS 111 Lab Manual

Posted: (0 seconds ago) Projects follow quickly after the readings and lectures in which the associated principles are presented. Project deliverables are spread (relatively) uniformly throughout the course (one per week). This is done to keep you from getting in trouble when you discover that you cannot complete a …

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Winter 2004 CS 31 (Shinnerl) Course Syllabus

Posted: (0 seconds ago) The official software platform for this course is Microsoft Visual Studio .NET on Microsoft Windows XP. If you wish to install the course software on your own computer, you may pick up your free copies of the installation CD's from Julie Austin at BH 2567, Mon--Fri 9am--4:30PM except 12--1PM lunch. Required Text: Absolute C++ by W. Savitch.

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Academic Integrity - University of California, Los Angeles

Posted: (0 seconds ago) Oct 04, 1999  · When in doubt, ask. Check your course syllabus or speak with your instructor for special requirements. Utilize resources for assistance. Helpful Resources (a) MLA Handbook for Writers of Research Papers, 3rd Edition. New York: Modern Language Association, 1984. (b) UCLA Department of English Style Sheet (available in the book store)

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CM229: Advanced Computational Genetics (Spring 2019)

Posted: (0 seconds ago) Course description. This is a graduate-level seminar course focusing on current topics in computational genetics. It is intended for PhD students with interest in research problems in computational genetics. Topics will cover problems in medical and population genetics, statistical models that are needed to make inferences in these problems ...

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