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Introduction to Computer Science
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Dear student! You are starting to learn about computation and its purpose. This course covers the same materials as an introductory class for undergraduate computer science majors. Its curriculum, which includes software, hardware and algorithms, resembles that of a one- or two-semester first-year college course or the high school Advanced Placement (AP) Computer Science. It does not require a formal computer science background.

Subject:
Computer Science
Material Type:
Textbook
Provider:
Wikibooks
Date Added:
09/22/2017
Introduction to Computer Science I
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CC BY
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This course will introduce students to the field of computer science and the fundamentals of computer programming. No prior programming experience is required. Upon successful completion of this course, students will be able to: Demonstrate an understanding of the history of computing as well as fundamental hardware and software concepts; Demonstrate an understanding of the programming life cycle; Explain how the JVM translates Java code into executable code; Demonstrate an understanding of Object-Oriented Programming concepts; Demonstrate an understanding of basic Java concepts by writing simple programs; Demonstrate an understanding of logical and relational operators as well as control structures; Demonstrate proficiency in basic Java I/O techniques by writing small programs. (Computer Science 101; See also: Mathematics 302)

Subject:
Computer Science
Material Type:
Full Course
Provider:
The Saylor Foundation
Date Added:
11/16/2011
Introduction to Computer Science II
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CC BY
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This course is a continuation of the first-semester course titled Introduction to Computer Science I. It will introduce the student to a number of more advanced Computer Science topics, laying a strong foundation for future academic study in the discipline. The student will begin with a comparison between Java--the programming language utilized last semester--and C++, another popular, industry-standard programming language. The student will then discuss the fundamental building blocks of Object-Oriented Programming, reviewing what they have learned learned last semester and familiarizing themselves with some more advanced programming concepts. The remaining course units will be devoted to various advanced topics, including the Standard Template Library, Exceptions, Recursion, Searching and Sorting, and Template Classes. By the end of the class, the student will have a solid understanding of Java and C++ programming, as well as a familiarity with the major issues that programmers routinely address in a professional setting. Upon successful completion of this course, the student will be able to: Demonstrate an understanding of the concepts of Java and C++ and how they are used in Object-Oriented Programming; Demonstrate an understanding of the history and development of Object-Oriented Programming; Explain the importance of the C++ Standard Template Library and how basic components are used; Demonstrate a basic understanding of the importance of run-time analysis in programming; Demonstrate an understanding of important sorting and search routines in programming; Demonstrate an understanding of the generic usage of templates in programming for C++ and Java; Compare and contrast the features of Java and C++. (Computer Science 102; See also: Mathematics 303)

Subject:
Computer Science
Material Type:
Full Course
Provider:
The Saylor Foundation
Date Added:
11/16/2011
Lecture 1: Probability and Statistics for Computer Science
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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:
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
Homework: Probability and Statistics for Computer Science - Week #10
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Homework 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:
Computer Science
Material Type:
Homework/Assignment
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Homework: Probability and Statistics for Computer Science - Week #11
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Homework 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:
Computer Science
Material Type:
Homework/Assignment
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Homework: Probability and Statistics for Computer Science - Week #2
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Homework 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:
Computer Science
Material Type:
Homework/Assignment
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Homework: Probability and Statistics for Computer Science - Week #5
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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:
Computer Science
Material Type:
Homework/Assignment
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Homework: Probability and Statistics for Computer Science - Week #8
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Homework 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:
Computer Science
Material Type:
Homework/Assignment
Provider:
CUNY Academic Works
Provider Set:
City College of New York
Author:
Evan Agovino
Nyc Tech-in-residence Corps
Date Added:
05/06/2020
Lecture 11: Probability and Statistics for Computer Science - "Linear Regression"
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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:
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
Exam: Probability and Statistics for Computer Science - "Midterm Exam Review"
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Midterm Exam Review 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:
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
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:
Computer Science
Material Type:
Full Course
Provider:
The Saylor Foundation
Date Added:
11/16/2011
Lecture 2: Probability and Statistics for Computer Science - "Descriptive Stats"
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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:
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
Lecture 7: Probability and Statistics for Computer Science - "Project Review"
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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:
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
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:
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
Lecture 5: Probability and Statistics for Computer Science - "Random Variables and Distribution"
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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:
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
Lecture 10: Probability and Statistics for Computer Science - "Relationships Between Variables"
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:
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
Computer Communications and Networks
Unrestricted Use
CC BY
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Detailed introduction to the basic hardware and software, architectural components for computer communications in local area networks. The components that are focused upon include understanding the basics of computer networks, switching, routing, protocols and security.

Subject:
Computer Science
Material Type:
Full Course
Provider:
The Saylor Foundation
Date Added:
11/16/2011
Computer Networks: A Systems Approach
Unrestricted Use
CC BY
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Suppose you want to build a computer network, one that has the potential to grow to global proportions and to support applications as diverse as teleconferencing, video on demand, electronic commerce, distributed computing, and digital libraries. What available technologies would serve as the underlying building blocks, and what kind of software architecture would you design to integrate these building blocks into an effective communication service? Answering this question is the overriding goal of this book—to describe the available building materials and then to show how they can be used to construct a network from the ground up.

Subject:
Computer Science
Material Type:
Textbook
Author:
Bruce Davie
Larry Peterson
Date Added:
09/12/2019
Lecture 9: Probability and Statistics for Computer Science - "Hypothesis Testing, Part Two"
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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:
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