MIT OCW- 6.00 Introduction to Computer Science and Programming

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MIT OCW- 6.00 Introduction to Computer Science and Programming (Size: 4.97 GB)
 quiz 1.pdf110.52 KB
 Quiz 2 Solution.pdf62 KB
 Quiz 2.pdf105.43 KB
 Quiz 3 Explanation.pdf23.82 KB
 Quiz 1 Solution.pdf71.58 KB
 Q3.py3.98 KB
 FINAL.pdf250.38 KB
 Final Topics.pdf40.21 KB
 Problem Set 5.pdf140.38 KB
 Problem Set 4.pdf91.1 KB
 shapes.txt193 bytes
 Problem Set 8.pdf91.05 KB
 PS10.py9.56 KB
 Problem Set 9.pdf140.83 KB
 Problem Set 3.pdf119.59 KB
 Problem Set 7.pdf29.2 KB
 Problem Set 12.pdf182.55 KB
 Problem Set 0.pdf51.76 KB
 Lecture20 Handout.pdf60.73 KB
 Lec20- Monte Carlo Simulations, Estimating pi.mp4204.08 MB
 Lecture20 Transcript.pdf98.25 KB
 Lec21- Validating Simulation Results.mp4229.12 MB
 Lecture21 Handout.pdf46.57 KB
 Lecture21 Transcript.pdf103.05 KB
 Lecture19 Transcript.pdf103.47 KB
 Lec19- Biased Random Walks, Distributions.mp4212.48 MB
 Lecture19 Handout.pdf24.41 KB
 Lecture18 Transcript.pdf100.52 KB
 Lecture18 Handout.pdf29.01 KB
 Lec18- Presenting Simulation Results, Pylab, Plotting.mp4225.32 MB
 Lecture24 Handout.pdf123.97 KB
 Lec24- Course Overview; What Do Computer Scientists Do.mp4182.47 MB
 Lecture24 Transcript.pdf110.39 KB
 Lecture23 Transcript.pdf107.96 KB
 Lecture23 Handout.pdf25.69 KB
 Lec23- Stock Market Simulation.mp4217.9 MB
 Lec22- Normal, Uniform, and Exponential Distributions.mp4216.46 MB
 Lecture22 Handout.pdf115.41 KB
 Lecture22 Transcript.pdf104.37 KB
 Lec11- Testing and Debugging.mp4208.64 MB
 Lecture11 Handout.pdf25.5 KB
 Lecture11 Transcript.pdf98.93 KB
 Lecture06 Handout.pdf103.74 KB
 Lecture06 Transcript.pdf106.76 KB
 Lec06- Bisection Methods, Newton_Raphson, Introduction to lists.mp4213.73 MB
 Lecture05- Transcript.pdf104.1 KB
 Lecture05- Handout.pdf72.61 KB
 Lec05- Floating Point Numbers, Successive Refinement.mp4188.31 MB
 Lec07- Lists and Mutability, Dictionaries.mp4197.46 MB
 Lecture07 Handout.pdf31.7 KB
 Lecture07 Transcript.pdf130.08 KB
 Lecture08 Transcript.pdf141.95 KB
 Lecture08 Handout.pdf31.7 KB
 Lec08- Complexity_ Log, Linear, Quadratic, Exponential Algorithms.mp4213.17 MB
 Lecture04 Transcript.pdf148.85 KB
 Lecture04 Handout.pdf33.76 KB
 Lec04- Abstraction through Functions; Introduction to Recursion.mp4219.17 MB
 Lecture02 Handout.pdf24.89 KB
 Lec02- Branching,Conditionals, and Iteration.mp4216.47 MB
 Lecture02 Transcript.pdf143.8 KB
 Lecture01 Transcript.pdf158.41 KB
 Lec 1- Introduction and Goals.mp4227.89 MB
 Lec03- Common Code Patterns- Iterative Programs.mp4217.2 MB
 Lecture03 Transcript.pdf140.1 KB
 Lecture03 Handout.pdf29.75 KB
 Lec09- Binary Search, Bubble and Selection Sorts.mp4202.3 MB
 Lecture09 Handout.pdf31.56 KB
 Lecture09 Transcript.pdf133.51 KB
 Lec15- Abstract Data Types, Classes and Methods.mp4214.7 MB
 Lecture15 Handout.pdf34.08 KB
 Lecture15 Transcript.pdf129.92 KB
 Lecture14 Transcript.pdf104.86 KB
 Lecture14 Handout.pdf25.35 KB
 Lec14- Introduction to Object-oriented Programming.mp4215.37 MB
 Lec16- Encapsulation, Inheritance, Shadowing.mp4214.59 MB
 Lecture16 Transcript.pdf125.29 KB
 Lecture16 Handout.pdf36.23 KB
 Lecture17 Handout.pdf28.64 KB
 Lec17- Computational Models-Random Walk Simulation.mp4210.35 MB
 Lecture17 Transcript.pdf106.88 KB
 Lecture13 Transcript.pdf95.18 KB
 Lecture13 Handout.pdf26.22 KB
 Lec13- Dynamic Programming.mp4208.39 MB
 Lecture10 Transcript.pdf132.18 KB
 Lecture10 Handout.pdf32.07 KB
 Lec10- Divide and Conquer Methods, Merge Sort, Exceptions.mp4197.25 MB
 Lecture12 Transcript.pdf109.04 KB
 Lecture12 Handout.pdf30.45 KB
 Lec12- Debugging, Knapsack Problem.mp4212.05 MB
 Sorting- How To.pdf125.4 KB
 Socket Programming- How To.pdf133.36 KB
 Python Tutorial.pdf622.44 KB
 Sums, Approximations, and Asymptotics II.pdf248.82 KB
 Regular Expression- How To.pdf181.33 KB
 The Python Library Reference.pdf9.44 MB
 Whats New In Python.pdf312.3 KB
 Unicode- How To.pdf161.85 KB
 The Python- C API.pdf1.41 MB
 Python Set-up and Usage.pdf385.87 KB
 MIT OCW Original Files ReadMe.txt686 bytes
 Torrent downloaded from Demonoid.com.txt47 bytes
 Readme.txt4.43 KB

Description

Uploader's Note: In this download is included all video lectures, video transcripts, lecture handouts, assignments
and exams for the MIT OCW Course 6.00 Introduction to Computer Science and Programming. All of these files can be
found and downloaded from the MIT OCW Site: http://ocw.mit.edu/index.htm


I did not have anything to do with this course, the recording or publishing of it or its materials. I have only
taken what MIT OCW was kind enough to give to the world and have compiled it into one large file. Hopefully making it available for those who can't stream the videos from their site.

Please remember to go to the website: http://ocw.mit.edu/index.htm and donate if at all possible to keep this
wonderful initiative going.

The videos are .mp4 and ranging in quality as they are downloaded from the MIT OCW site.
If this is fairly popular I will be doing more, so if you go to the website and see any courses you would like done in this style feel free to hit me up.

6.00 Introduction to Computer Science and Programming
As taught in: Fall 2008

Level: Undergraduate

Instructors:

Prof. Eric Grimson

Prof. John Guttag


Course Description:

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 PythonΓΓÇ₧ó programming language.

**Warning: On the Python homepage, the latest version available for download is actually 3.0. Do not install this!
This version is not backwards compatible with the code that you'll be writing in this course
(for example, you have to type print("test") instead of print test.)**


MIT OpenCourseWare (OCW)

Unlocking Knowledge,Empowering Minds.
Free lecture notes, exams, and videos from MIT. No registration required.

MIT OpenCourseWare (OCW) is a web-based publication of virtually all MIT course content.
OCW is open and available to the world and is a permanent MIT activity.


What is MIT OpenCourseWare?

MIT OpenCourseWare is a free publication of MIT course materials that reflects almost all the
undergraduate and graduate subjects taught at MIT.

* OCW is not an MIT education.
* OCW does not grant degrees or certificates.
* OCW does not provide access to MIT faculty.
* Materials may not reflect entire content of the course.

What it takes to support this work:

Each course we publish requires an investment of $10,000 to $15,000 to compile course materials from faculty,
ensure proper licensing for open sharing, and format materials for global distribution.
Courses with video content cost about twice as much, but your feedback about the significant value of these
video materials helps to justify the cost. (From the MIT OCW Website: http://ocw.mit.edu/about/ )

MIT OCW Homepage: http://ocw.mit.edu/index.htm

MIT OCW Creative Commons License: http://ocw.mit.edu/terms/index.htm#cc


*Citation:
Eric Grimson and John Guttag, 6.00 Introduction to Computer Science and Programming, Fall 2008.
(Massachusetts Institute of Technology: MIT OpenCourseWare). http://ocw.mit.edu (accessed 01 10, 2011).
License: Creative Commons Attribution-Noncommercial-Share Alike.


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MIT OCW- 6.00 Introduction to Computer Science and Programming