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Computer Buying Project
Unrestricted Use
CC BY
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For this 3-part project, students will practice using the problem-solving steps by pretending to help a family member or friend who has asked them to give a recommendation of which computer to buy.

Subject:
Computer Science
Material Type:
Homework/Assignment
Author:
Becky Ball
Crystal Van Ausdal
Date Added:
02/27/2020
Lecture 2: Probability and Statistics for Computer Science - "Descriptive Stats"
Conditional Remix & Share Permitted
CC BY-NC-SA
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Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Subject:
Applied Science
Computer Science
Material Type:
Lecture
Lecture Notes
Lesson Plan
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Agovino Evan
Cuny City College
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Computer Architecture
Unrestricted Use
CC BY
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The purpose of this course is to cultivate an understanding of modern computing technology through an in-depth study of the interface between hardware and software. The student will study the history of modern computing technology before learning about modern computer architecture, then the recent switch from sequential processing to parallel processing. Upon completion of this course, students will be able to: identify important advances that have taken place in the history of modern computing and discuss some of the latest trends in computing industry; explain how programs written in high-level programming language, such as C or Java, can be translated into the language of the hardware; describe the interface between hardware and software and explain how software instructs hardware to accomplish desired functions; demonstrate an understanding of the process of carrying out sequential logic design; demonstrate an understanding of computer arithmetic hardware blocks and floating point representation; explain how a hardware programming language is executed on hardware and how hardware and software design affect performance; demonstrate an understanding of the factors that determine the performance of a program; demonstrate an understanding of the techniques that designers use to improve the performance of programs running on hardware; demonstrate an understanding of the importance of memory hierarchy in computer design and explain how memory design impacts overall hardware performance; demonstrate an understanding of storage and I/O devices, their performance measurement, and redundant array of inexpensive disks (more commonly referred to by the acronym RAID) technology; list the reasons for and the consequences of the recent switch from sequential processing to parallel processing in hardware manufacture and explain the basics of parallel programming. (Computer Science 301)

Subject:
Applied Science
Computer Science
Material Type:
Full Course
Provider:
The Saylor Foundation
Date Added:
11/16/2011
Computer Histories - An introductory course on the history of computing
Conditional Remix & Share Permitted
CC BY-NC-SA
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Computer Histories is an introductory course on the history of computing that explores the questions 1) What is the history of computing? 2) What is the future of computing? and 3) What lessons can we learn from computing's past that will help guide us in determining computing's future?

Subject:
Applied Science
History
Material Type:
Full Course
Author:
Michael P. D'Alessandro M.D.
Date Added:
09/07/2016
Theory of Computation
Conditional Remix & Share Permitted
CC BY-NC-SA
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This course emphasizes computability and computational complexity theory. Topics include regular and context-free languages, decidable and undecidable problems, reducibility, recursive function theory, time and space measures on computation, completeness, hierarchy theorems, inherently complex problems, oracles, probabilistic computation, and interactive proof systems.

Subject:
Applied Science
Computer Science
Engineering
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Sipser, Michael
Date Added:
09/01/2020
Exam: Probability and Statistics for Computer Science - "Practice Final Exam"
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CC BY-NC-SA
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Practice Final Exam for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Subject:
Applied Science
Computer Science
Material Type:
Assessment
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Topics in Theoretical Computer Science : Internet Research Problems
Conditional Remix & Share Permitted
CC BY-NC-SA
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We will discuss numerous research problems that are related to the internet. Sample topics include: routing algorithms such as BGP, communication protocols such as TCP, algorithms for intelligently selecting a resource in the face of uncertainty, bandwidth sensing tools, load balancing algorithms, streaming protocols, determining the structure of the internet, cost optimization, DNS-related problems, visualization, and large-scale data processing. The seminar is intended for students who are ready to work on challenging research problems. Each lecture will discuss:

methods used today
issues and problems
formulation of concrete problems
potential new lines of research

A modest amount of background information will be provided so that the importance and context of the problems can be understood. No previous study of the internet is required, but experience with algorithms and/or theoretical computer science at the graduate/research level is needed.

Subject:
Applied Science
Career and Technical Education
Computer Science
Electronic Technology
Engineering
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Leighton, Tom
Maggs, Bruce
Sundaram, Ravi
Teng, Shang-Hua
Date Added:
02/01/2002
Lecture 7: Probability and Statistics for Computer Science - "Project Review"
Conditional Remix & Share Permitted
CC BY-NC-SA
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Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Subject:
Applied Science
Computer Science
Material Type:
Lecture
Lecture Notes
Lesson Plan
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Computational Science and Engineering I
Conditional Remix & Share Permitted
CC BY-NC-SA
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This course provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and applications.
Note: This course was previously called "Mathematical Methods for Engineers I."

Subject:
Algebra
Applied Science
Computer Science
Engineering
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Strang, Gilbert
Date Added:
09/01/2008
Introduction to computer
Conditional Remix & Share Permitted
CC BY-NC-SA
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OBJECTIVES:To know what is a computerTo be familiar with the history of computers.To identify the different types of computers.To identify the hardware components of a computer. 

Subject:
Computer Science
Information Science
Material Type:
Diagram/Illustration
Lecture
Module
Author:
alovi zhimomi
Date Added:
09/08/2020
Future of Computing
Conditional Remix & Share Permitted
CC BY-NC-SA
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0.0 stars

This unit covers five topics concerning the future of computing: trends in computing, interfaces used to communicate with computer systems, cloud computing, the changing social implications of the use of computer systems, and the ubiquity of computers in our daily lives.

Subject:
Applied Science
Health, Medicine and Nursing
Material Type:
Lecture
Provider:
Open Michigan
Provider Set:
Health IT Workforce Curriculum
Author:
Oregon Health & Science University
Date Added:
09/26/2014
Ten Simple Rules for Reproducible Computational Research
Unrestricted Use
CC BY
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Replication is the cornerstone of a cumulative science. However, new tools and technologies, massive amounts of data, interdisciplinary approaches, and the complexity of the questions being asked are complicating replication efforts, as are increased pressures on scientists to advance their research. As full replication of studies on independently collected data is often not feasible, there has recently been a call for reproducible research as an attainable minimum standard for assessing the value of scientific claims. This requires that papers in experimental science describe the results and provide a sufficiently clear protocol to allow successful repetition and extension of analyses based on original data. The importance of replication and reproducibility has recently been exemplified through studies showing that scientific papers commonly leave out experimental details essential for reproduction, studies showing difficulties with replicating published experimental results, an increase in retracted papers, and through a high number of failing clinical trials. This has led to discussions on how individual researchers, institutions, funding bodies, and journals can establish routines that increase transparency and reproducibility. In order to foster such aspects, it has been suggested that the scientific community needs to develop a “culture of reproducibility” for computational science, and to require it for published claims. We want to emphasize that reproducibility is not only a moral responsibility with respect to the scientific field, but that a lack of reproducibility can also be a burden for you as an individual researcher. As an example, a good practice of reproducibility is necessary in order to allow previously developed methodology to be effectively applied on new data, or to allow reuse of code and results for new projects. In other words, good habits of reproducibility may actually turn out to be a time-saver in the longer run. We further note that reproducibility is just as much about the habits that ensure reproducible research as the technologies that can make these processes efficient and realistic. Each of the following ten rules captures a specific aspect of reproducibility, and discusses what is needed in terms of information handling and tracking of procedures. If you are taking a bare-bones approach to bioinformatics analysis, i.e., running various custom scripts from the command line, you will probably need to handle each rule explicitly. If you are instead performing your analyses through an integrated framework (such as GenePattern, Galaxy, LONI pipeline, or Taverna), the system may already provide full or partial support for most of the rules. What is needed on your part is then merely the knowledge of how to exploit these existing possibilities.

Subject:
Applied Science
Computer Science
Information Science
Material Type:
Reading
Provider:
PLOS Computational Biology
Author:
Anton Nekrutenko
Eivind Hovig
Geir Kjetil Sandve
James Taylor
Date Added:
08/07/2020
Lecture 5: Probability and Statistics for Computer Science - "Random Variables and Distribution"
Conditional Remix & Share Permitted
CC BY-NC-SA
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Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Subject:
Applied Science
Computer Science
Material Type:
Lecture
Lecture Notes
Lesson Plan
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Computing Life
Unrestricted Use
Public Domain
Rating
0.0 stars

A 24-page booklet that showcases the exciting ways that scientists are using the power of computers to expand our knowledge of biology and medicine. (National Institute of General Medical Sciences)

Subject:
Biology
Life Science
Material Type:
Reading
Provider:
National Institutes of Health
Date Added:
07/01/2013
Cultures of Computing
Conditional Remix & Share Permitted
CC BY-NC-SA
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0.0 stars

This course examines computers anthropologically, as artifacts revealing the social orders and cultural practices that create them. Students read classic texts in computer science along with cultural analyses of computing history and contemporary configurations. It explores the history of automata, automation and capitalist manufacturing; cybernetics and WWII operations research; artificial intelligence and gendered subjectivity; robots, cyborgs, and artificial life; creation and commoditization of the personal computer; the growth of the Internet as a military, academic, and commercial project; hackers and gamers; technobodies and virtual sociality. Emphasis is placed on how ideas about gender and other social differences shape labor practices, models of cognition, hacking culture, and social media.

Subject:
Anthropology
Arts and Humanities
History
Philosophy
Social Science
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Helmreich, Stefan
Date Added:
09/01/2011
Computer Science resources for lower Primary teachers
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CC BY-NC
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0.0 stars

This resource contains several ready made curricula for lower primary students. The resources are easy to use and contain all of the information a teacher would need to teach the lessons/units.

Subject:
Computer Science
Material Type:
Activity/Lab
Author:
Sara Fernández
Date Added:
12/10/2020
Introduction to Electrical Engineering and Computer Science I
Conditional Remix & Share Permitted
CC BY-NC-SA
Rating
0.0 stars

This course provides an integrated introduction to electrical engineering and computer science, taught using substantial laboratory experiments with mobile robots. Our primary goal is for you to learn to appreciate and use the fundamental design principles of modularity and abstraction in a variety of contexts from electrical engineering and computer science.
Our second goal is to show you that making mathematical models of real systems can help in the design and analysis of those systems. Finally, we have the more typical goals of teaching exciting and important basic material from electrical engineering and computer science, including modern software engineering, linear systems analysis, electronic circuits, and decision-making.
Course Format
This course has been designed for independent study. It includes all of the materials you will need to understand the concepts covered in this subject. The materials in this course include:

Lecture videos from Spring 2011, taught by Prof. Dennis Freeman
Recitation videos, developed for OCW Scholar by teaching assistant Kendra Pugh
Course notes
Software and design labs
Homework assignments and additional exercises
Nano-quizzes and exams with solutions

Content Development
Leslie Kaelbling 
Jacob White 
Harold Abelson 
Dennis Freeman
Tomás Lozano-Pérez 
Isaac Chuang

Subject:
Applied Science
Career and Technical Education
Computer Science
Electronic Technology
Engineering
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Abelson, Harold
Chuang, Isaac
Freeman, Dennis
Kaelbling, Leslie
Lozano-Pérez, Tomás
White, Jacob
Date Added:
02/01/2011
Culturally Responsive-Sustaining Computer Science Education: A Framework
Only Sharing Permitted
CC BY-NC-ND
Rating
0.0 stars

The framework was developed by the Kapor Center to bring a focus to equity in Computer Science Education, specifically around teacher preparation, professional development, curriculum development, and policy-making.

Subject:
Applied Science
Computer Science
Material Type:
Primary Source
Author:
Kapor Center
Date Added:
06/28/2022