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University - IT and Computing

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  Accessibility in interaction design (M364_1) Summary 15
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An introduction to data and information (M150_2) Summary 20
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  An introduction to e-commerce and distributed applications (M360_1) Summary 8
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  • Artificial Intelligence – Introduction to RoboticsYouTubeiTunesMultiple formats – Oussama Khatib, Stanford
  • Artificial Intelligence – Natural Language ProcessingMultiple formats – Christopher Manning, Stanford
  • Artificial Intelligence – Machine LearningYouTubeiTunesMultiple formats – Andrew Ng, Stanford
  • Artificial IntelligenceYouTube – P.Dasgupta, IIT
  • BitsMultiple Formats – Harry Lewis, Harvard
  • Building Dynamic Web SitesVideo & AudioRss FeediTunes - David Malan, Harvard Extension
  • Computer GraphicsYouTube – Sukhendu Das, IIT
  • Computer NetworksYouTube – S.Ghosh, IIT
  • Computer Science 1Feed – UCLA
  • Computer System EngineeringWeb Site – Profs. Robert Morris and Samuel Madden, MIT
  • Discrete Mathematical Structures YouTube – Kamala Krithivasan, IIT
  • Intensive Introduction to Computer Science Using C, PHP, and JavaScript – Multiple Formats – David Malan, Harvard
  • Introduction to Computer Science and Programming - YouTubeiTunes – Eric Grimson, John Guttag, MIT
  • Introduction to Computer Science: Programming MethodologyYouTubeiTunesMultiple formats – Mehran Sahami, Stanford
  • Introduction to Computer Science: Programming Abstractions - YouTubeiTunes - Multiple formats – Julie Zelenski, Stanford
  • Introduction to Computer Science: Programming Paradigms - YouTubeiTunes - Multiple formats – Jerry Cain, Stanford
  • Introduction to ComputersFeed – Americ Azevedo, UC Berkeley
  • Introduction to Computer GraphicsYouTube – Prem Kalra, IIT
  • Introduction to Problem Solving & ProgrammingYouTube – Deepak Gupta, IIT
  • iPhone Application Development (Spring 2009)- iTunes – Stanford
  • iPhone Application Development (Winter 2010)iTunes – Stanford
  • Multimedia Systems - iTunes – Surendar Chandra, Notre Dame
  • Operating Systems and System ProgrammingiTunesFeed – Multiple professors, UC Berkeley
  • Operating Systems PrinciplesiTunes – Surendar Chandra, Notre Dame
  • Principles of Digital Communications I - YouTubeiTunes – Profs Gallagher and Zheng, MIT
  • Principles of Digital Communications II - YouTube – MIT
  • The Future of the InternetiTunes – Ramesh Johari, Stanford
  • The Structure and Interpretation of Computer ProgramsiTunesVideo FeedStream – Brian Harvey
  • Understanding Computers and the InternetiTunesFeed – David Malan, Harvard University
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  Computers and computer systems (T224_1) Summary 20
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6.01 Introduction to Electrical Engineering and Computer Science I (MIT)

07 July 2010, 07:41:45 | Leslie Kaelbling
6.01 explores fundamental ideas in electrical engineering and computer science, in the context of working with mobile robots. Key engineering principles, such as abstraction and modularity, are applied in the design of computer programs, electronic circuits, discrete-time controllers, and noisy and/or uncertain systems.

29 June 2010, 10:41:11 | Dennis Freeman
6.003 covers the fundamentals of signal and system analysis, focusing on representations of discrete-time and continuous-time signals (singularity functions, complex exponentials and geometrics, Fourier representations, Laplace and Z transforms, sampling) and representations of linear, time-invariant systems (difference and differential equations, block diagrams, system functions, poles and zeros, convolution, impulse and step responses, frequency responses). Applications are drawn broadly from engineering and physics, including feedback and control, communications, and signal processing.
28 June 2010, 10:42:27 | Daniel Weller
This course provides a thorough introduction to the C programming language, the workhorse of the UNIX operating system and lingua franca of embedded processors and micro-controllers. The first two weeks will cover basic syntax and grammar, and expose students to practical programming techniques. The remaining lectures will focus on more advanced concepts, such as dynamic memory allocation, concurrency and synchronization, UNIX signals and process control, library development and usage. Daily programming assignments and weekly laboratory exercises are required. Knowledge of C is highly marketable for summer internships, UROPs, and full-time positions in software and embedded systems development.
  
22 June 2010, 11:07:16 | Nancy Lynch
Distributed algorithms are algorithms designed to run on multiple processors, without tight centralized control. In general, they are harder to design and harder to understand than single-processor sequential algorithms. Distributed algorithms are used in many practical systems, ranging from large computer networks to multiprocessor shared-memory systems. They also have a rich theory, which forms the subject matter for this course. The core of the material will consist of basic distributed algorithms and impossibility results, as covered in Prof. Lynch's book Distributed Algorithms. This will be supplemented by some updated material on topics such as self-stabilization, wait-free computability, and failure detectors, and some new material on scalable shared-memory concurrent programming.
 
10 May 2010, 12:00:11 | Evan Jones
This course is an introduction to software engineering, using the Java™ programming language. It covers concepts useful to 6.005. Students will learn the fundamentals of Java. The focus is on developing high quality, working software that solves real problems. The course is designed for students with some programming experience, but if you have none and are motivated you will do fine. Students who have taken 6.005 should not take this course. Each class is composed of one hour of lecture and one hour of assisted lab work. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.
  
07 May 2010, 08:35:57 | Charles Leiserson
Modern computing platforms provide unprecedented amounts of raw computational power. But significant complexity comes along with this power, to the point that making useful computations exploit even a fraction of the potential of the computing platform is a substantial challenge. Indeed, obtaining good performance requires a comprehensive understanding of all layers of the underlying platform, deep insight into the computation at hand, and the ingenuity and creativity required to obtain an effective mapping of the computation onto the machine. The reward for mastering these sophisticated and challenging topics is the ability to make computations that can process large amount of data orders of magnitude more quickly and efficiently and to obtain results that are unavailable with standard practice. This class is a hands-on, project-based introduction to building scalable and high-performance software systems. Topics include: performance analysis, algorithmic techniques for high performance, instruction-level optimizations, cache and memory hierarchy optimization, parallel programming, and building scalable distributed systems.

03 May 2010, 04:39:06 | Soheil Feizi-Khankandi
The course serves as an introduction to the theory and practice behind many of today's communications systems. 6.450 forms the first of a two-course sequence on digital communication. The second class, 6.451 Principles of Digital Communication II, is offered in the spring. Topics covered include: digital communications at the block diagram level, data compression, Lempel-Ziv algorithm, scalar and vector quantization, sampling and aliasing, the Nyquist criterion, PAM and QAM modulation, signal constellations, finite-energy waveform spaces, detection, and modeling and system design for wireless communication.
29 April 2010, 12:57:40 | Clifton Fonstad, Jr
6.012 is the header course for the department's "Devices, Circuits and Systems" concentration. The topics covered include modeling of microelectronic devices, basic microelectronic circuit analysis and design, physical electronics of semiconductor junction and MOS devices, relation of electrical behavior to internal physical processes, development of circuit models, and understanding the uses and limitations of various models. The course uses incremental and large-signal techniques to analyze and design bipolar and field effect transistor circuits, with examples chosen from digital circuits, single-ended and differential linear amplifiers, and other integrated circuits.

Ever hang your head in shame after your Python program wasn't as fast as your friend's C program? Ever wish you could use objects without having to use Java? Join us for this fun introduction to C and C++! We will take you through a tour that will start with writing simple C programs, go deep into the caves of C memory manipulation, resurface with an introduction to using C++ classes, dive deeper into advanced C++ class use and the C++ Standard Template Libraries. We'll wrap up by teaching you some tricks of the trade that you may need for tech interviews. We see this as a "C/C++ empowerment" course: we want you to come away understanding why you would want to use C over another language (control over memory, probably for performance reasons), why you would want to use C++ rather than C (objects), and how to be useful in C and C++. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.
This course focuses on the algorithmic and machine learning foundations of computational biology, combining theory with practice. We study the principles of algorithm design for biological datasets, and analyze influential problems and techniques. We use these to analyze real datasets from large-scale studies in genomics and proteomics. The topics covered include: Genomes: biological sequence analysis, hidden Markov models, gene finding, RNA folding, sequence alignment, genome assembly Networks: gene expression analysis, regulatory motifs, graph algorithms, scale-free networks, network motifs, network evolution Evolution: comparative genomics, phylogenetics, genome duplication, genome rearrangements, evolutionary theory, rapid evolution.
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Crossing the boundary - analogue universe, digital worlds (M150_1) Summary 20
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  Data and processes in computing (M263_1) Summary 14
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  Designing the user interface: text, colour, images, moving images and sound (M873_1) Summary 4
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Finding information in information technology and computing (LIB_5) Summary 9

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