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Introduction to Computer Science I

Introduction to Computer Science I

Computer Science 50: Introduction to Computer Science I is a first course ... (more)

Computer Science 50: Introduction to Computer Science I is a first course in computer science at Harvard College for concentrators and non-concentrators alike. More than just teach you how to program, this course teaches you how to think more methodically and how to solve problems more effectively. As such, its lessons are applicable well beyond the boundaries of computer science itself. That the course does teach you how to program, though, is perhaps its most empowering return. With this skill comes the ability to solve real-world problems in ways and at speeds beyond the abilities of most humans. (less)

Subject:
Science and Technology
Material Type:
Activities and Labs
Assessments
Full Course
Video Lectures
Collection:
Harvard University
Provider:
Harvard University
Author:
David Malan
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Mathematics for Computer Science, Spring 2005

Mathematics for Computer Science, Spring 2005

Mathematical tools and methods for computer science and engineering. Emphasis on development ... (more)

Mathematical tools and methods for computer science and engineering. Emphasis on development of rigorous thinking, analytical skills, and mathematical sophistication while learning elementary discrete mathematics. Topics: mathematical proofs; induction and well-ordering; divisibility and congruences; asymptotic notation and growth of functions; sets, relations, functions, and graphs; counting theory; recurrences and generating functions; and discrete probability. (less)

Subject:
Science and Technology
Material Type:
Activities and Labs
Assessments
Full Course
Homework and Assignments
Lecture Notes
Syllabi
Teaching and Learning Strategies
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
Devadas, Srinivas
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Introduction to Computer Science: Programming Paradigms

Introduction to Computer Science: Programming Paradigms

Advanced memory management features of C and C++; the differences between imperative ... (more)

Advanced memory management features of C and C++; the differences between imperative and object-oriented paradigms. The functional paradigm (using LISP) and concurrent programming (using C and C++). Brief survey of other modern languages such as Python, Objective C, and C#. (less)

Subject:
Science and Technology
Material Type:
Audio Lectures
Full Course
Lecture Notes
Video Lectures
Collection:
Stanford University - School of Engineering
Provider:
Stanford University
Author:
Jerry Cain
No Strings Attached
Intensive Introduction to Computer Science

Intensive Introduction to Computer Science

This free online computer science course is an introduction to the intellectual ... (more)

This free online computer science course is an introduction to the intellectual enterprises of computer science. Topics include algorithms (their design, implementation, and analysis); software development (abstraction, encapsulation, data structures, debugging, and testing); architecture of computers (low-level data representation and instruction processing); computer systems (programming languages, compilers, operating systems, and databases); and computers in the real world (networks, websites, security, forensics, and cryptography). The course teaches students how to think more carefully and how to solve problems more effectively. Problem sets involve extensive programming in C as well as PHP and JavaScript. (less)

Subject:
Science and Technology
Material Type:
Audio Lectures
Video Lectures
Collection:
Harvard Extension School
Provider:
Harvard Extension School
Author:
David J. Malan
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Computer Science, Spring 2008

Computer Science, Spring 2008

UCB course videos for CS 61A The Structure and Interpretation of Computer ... (more)

UCB course videos for CS 61A The Structure and Interpretation of Computer Programs, Fall 2007. Introduction to programming and computer science. This course exposes students to techniques of abstraction at several levels: (a) within a programming language, using higher-order functions, manifest types, data-directed programming, and message-passing; (b) between programming languages, using functional and rule-based languages as examples. It also relates these techniques to the practical problems of implementation of languages and algorithms on a von Neumann machine. There are several significant programming projects, programmed in a dialect of the LISP language. (less)

Subject:
Science and Technology
Material Type:
Full Course
Video Lectures
Collection:
UC Berkeley Webcast
Provider:
U.C. Berkeley
Author:
Brian Harvey
Introduction to Computer Science I

Introduction to Computer Science I

This course will introduce students to the field of computer science and ... (more)

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) (less)

Subject:
Science and Technology
Material Type:
Activities and Labs
Assessments
Full Course
Homework and Assignments
Readings
Syllabi
Collection:
Saylor Foundation
Provider:
The Saylor Foundation
Read the Fine Print
Mathematics for Computer Science

Mathematics for Computer Science

A basic introduction to Calculus and Linear Algebra. The goal is to ... (more)

A basic introduction to Calculus and Linear Algebra. The goal is to make students mathematically literate in preparation for studying a scientific/engineering discipline. The first week covers differential calculus: graphing functions, limits, derivatives, and applying differentiation to real-world problems, such as maximization and rates of change. The second week covers integral calculus: sums, integration, areas under curves and computing volumes. This is not meant to be a comprehensive calculus course, but rather an introduction to the fundamental concepts. The third and fourth weeks introduce some basic linear algebra: vector spaces, linear transformations, matrices, matrix operations, and diagonalization. The emphasis will be on using the results, not on their proofs. (less)

Subject:
Mathematics and Statistics
Science and Technology
Material Type:
Assessments
Full Course
Homework and Assignments
Readings
Other
Collection:
ArsDigita University
Provider:
ArsDigita University
Author:
Tara Holm
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Introduction to Computer Science: Programming Abstractions

Introduction to Computer Science: Programming Abstractions

This course is the natural successor to Programming Methodology and covers such ... (more)

This course is the natural successor to Programming Methodology and covers such advanced programming topics as recursion, algorithmic analysis, and data abstraction using the C++ programming language, which is similar to both C and Java. If you've taken the Computer Science AP exam and done well (scored 4 or 5) or earned a good grade in a college course, Programming Abstractions may be an appropriate course for you to start with, but often Programming Abstractions (Accelerated) is a better choice. Programming Abstractions assumes that you already have familiarity with good programming style and software engineering issues (at the level of Programming Methodology), and that you can use this understanding as a foundation on which to tackle new topics in programming and data abstraction. (less)

Subject:
Science and Technology
Material Type:
Audio Lectures
Full Course
Lecture Notes
Video Lectures
Collection:
Stanford University - School of Engineering
Provider:
Stanford University
Author:
Julie Zelenski
No Strings Attached
Mathematics for Computer Science, Spring 2010

Mathematics for Computer Science, Spring 2010

This subject offers an introduction to Discrete Mathematics oriented toward Computer Science ... (more)

This subject offers an introduction to Discrete Mathematics oriented toward Computer Science and Engineering. The subject coverage divides roughly into thirds: Fundamental concepts of mathematics: definitions, proofs, sets, functions, relations. Discrete structures: graphs, state machines, modular arithmetic, counting. Discrete probability theory. On completion of 6.042, students will be able to explain and apply the basic methods of discrete (noncontinuous) mathematics in Computer Science. They will be able to use these methods in subsequent courses in the design and analysis of algorithms, computability theory, software engineering, and computer systems. (less)

Subject:
Mathematics and Statistics
Science and Technology
Material Type:
Assessments
Homework and Assignments
Lecture Notes
Readings
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
Meyer, Albert R.
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Mathematics for Computer Science, Fall 2010

Mathematics for Computer Science, Fall 2010

This course covers elementary discrete mathematics for computer science and engineering. It ... (more)

This course covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions. (less)

Subject:
Mathematics and Statistics
Science and Technology
Material Type:
Assessments
Homework and Assignments
Readings
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
Dijk, Marten van
Leighton, Tom
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Introduction to Computer Science: Programming Methodology

Introduction to Computer Science: Programming Methodology

This course is the largest of the introductory programming courses and is ... (more)

This course is the largest of the introductory programming courses and is one of the largest courses at Stanford. Topics focus on the introduction to the engineering of computer applications emphasizing modern software engineering principles: object-oriented design, decomposition, encapsulation, abstraction, and testing. Programming Methodology teaches the widely-used Java programming language along with good software engineering principles. Emphasis is on good programming style and the built-in facilities of the Java language. The course is explicitly designed to appeal to humanists and social scientists as well as hard-core techies. In fact, most Programming Methodology graduates end up majoring outside of the School of Engineering. (less)

Subject:
Science and Technology
Material Type:
Audio Lectures
Full Course
Video Lectures
Collection:
Stanford University - School of Engineering
Provider:
Stanford University
Author:
Mehran Sahami
No Strings Attached
Mathematics for Computer Science, Fall 2005

Mathematics for Computer Science, Fall 2005

Mathematical tools and methods for computer science and engineering. Emphasis on development ... (more)

Mathematical tools and methods for computer science and engineering. Emphasis on development of rigorous thinking, analytical skills, and mathematical sophistication while learning elementary discrete mathematics. Topics: mathematical proofs; induction and well-ordering; divisibility and congruences; asymptotic notation and growth of functions; sets, relations, functions, and graphs; counting theory; recurrences and generating functions; and discrete probability. This is an introductory course in Discrete Mathematics oriented toward Computer Science and Engineering. The course divides roughly into thirds: Fundamental Concepts of Mathematics: Definitions, Proofs, Sets, Functions, Relations Discrete Structures: Modular Arithmetic, Graphs, State Machines, Counting Discrete Probability Theory. (less)

Subject:
Science and Technology
Material Type:
Assessments
Full Course
Homework and Assignments
Lecture Notes
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
Meyer, Albert R.
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Computational Cognitive Science, Fall 2004

Computational Cognitive Science, Fall 2004

This course is an introduction to computational theories of human cognition. Drawing ... (more)

This course is an introduction to computational theories of human cognition. Drawing on formal models from classic and contemporary artificial intelligence, students will explore fundamental issues in human knowledge representation, inductive learning and reasoning. What are the forms that our knowledge of the world takes? What are the inductive principles that allow us to acquire new knowledge from the interaction of prior knowledge with observed data? What kinds of data must be available to human learners, and what kinds of innate knowledge (if any) must they have? (less)

Subject:
Science and Technology
Material Type:
Activities and Labs
Full Course
Homework and Assignments
Lecture Notes
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
Tenenbaum, Joshua
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Computational Cognitive Science, Spring 2003

Computational Cognitive Science, Spring 2003

An introduction to computational theories of human cognition. Emphasizes questions of inductive ... (more)

An introduction to computational theories of human cognition. Emphasizes questions of inductive learning and inference, and the representation of knowledge. Project required for graduate credit. This class is suitable for intermediate to advanced undergraduates or graduate students specializing in cognitive science, artificial intelligence, and related fields. (less)

Subject:
Science and Technology
Material Type:
Full Course
Homework and Assignments
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
Tenenbaum, Joshua
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Introduction to Computer Science and Programming, Fall 2007

Introduction to Computer Science and Programming, Fall 2007

This subject is aimed at students with little or no programming experience. ... (more)

This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python programming language. (less)

Subject:
Science and Technology
Material Type:
Assessments
Full Course
Homework and Assignments
Lecture Notes
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
Guttag, John
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Introduction to Computer Science and Programming, Spring 2011

Introduction to Computer Science and Programming, Spring 2011

This subject is aimed at students with little or no programming experience. ... (more)

This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python programming language. (less)

Subject:
Science and Technology
Material Type:
Full Course
Homework and Assignments
Readings
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
John Guttag
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Introduction to Computer Science and Programming, Fall 2008

Introduction to Computer Science and Programming, Fall 2008

"This subject is aimed at students with little or no programming experience. ... (more)

"This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python‰ă˘ programming language." (less)

Subject:
Science and Technology
Material Type:
Activities and Labs
Assessments
Full Course
Video Lectures
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
Grimson, Eric
Guttag, John
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Great Ideas in Theoretical Computer Science, Spring 2008

Great Ideas in Theoretical Computer Science, Spring 2008

This course provides a challenging introduction to some of the central ideas ... (more)

This course provides a challenging introduction to some of the central ideas of theoretical computer science. It attempts to present a vision of "computer science beyond computers": that is, CS as a set of mathematical tools for understanding complex systems such as universes and minds. Beginning in antiquity--with Euclid's algorithm and other ancient examples of computational thinking--the course will progress rapidly through propositional logic, Turing machines and computability, finite automata, GĚŚdel's theorems, efficient algorithms and reducibility, NP-completeness, the P versus NP problem, decision trees and other concrete computational models, the power of randomness, cryptography and one-way functions, computational theories of learning, interactive proofs, and quantum computing and the physical limits of computation. Class participation is essential, as the class will include discussion and debate about the implications of many of these ideas. (less)

Subject:
Science and Technology
Material Type:
Full Course
Homework and Assignments
Lecture Notes
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
Aaronson, Scott
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Computational Sciences Lecture Series at UW-Madison

Computational Sciences Lecture Series at UW-Madison

The goal of the Computational Sciences Lecture Series (CSLS) is to bring ... (more)

The goal of the Computational Sciences Lecture Series (CSLS) is to bring together researchers from mathematics (pure and applied), computer science, physics, and engineering to promote cross-fertilization between these fields and to establish computational science as an active research discipline at UW-Madison. The CSLS will consist of several half-day meetings during each year, each meeting consisting of three lectures by distinguished researchers, grouped around a common theme. (less)

Subject:
Science and Technology
Material Type:
Full Course
Readings
Syllabi
Collection:
Connexions
Provider:
Rice University
Author:
Pascal Vontobel
No Strings Attached
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Subject:
Science and Technology
Material Type:
Assessments
Full Course
Homework and Assignments
Lecture Notes
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
George Kocur
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