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S# Lecture Course Institute Instructor Discipline
3201
Project Global Illumination
Multicore Programming Primer (M-I-T) MIT Prof. Dr. Rodric Rabbah, Prof. Dr. Saman Amarasinghe Applied Sciences
3202
StreamIt Language
Multicore Programming Primer (M-I-T) MIT Prof. Dr. Rodric Rabbah, Prof. Dr. Saman Amarasinghe Applied Sciences
3203
Project Molecular Dynamics
Multicore Programming Primer (M-I-T) MIT Prof. Dr. Rodric Rabbah, Prof. Dr. Saman Amarasinghe Applied Sciences
3204
StreamIt Parallelizing Compiler
Multicore Programming Primer (M-I-T) MIT Prof. Dr. Rodric Rabbah, Prof. Dr. Saman Amarasinghe Applied Sciences
3205
Project Software Radio
Multicore Programming Primer (M-I-T) MIT Prof. Dr. Rodric Rabbah, Prof. Dr. Saman Amarasinghe Applied Sciences
3206
Synthesizing Parallel Programs
Multicore Programming Primer (M-I-T) MIT Prof. Dr. Rodric Rabbah, Prof. Dr. Saman Amarasinghe Applied Sciences
3207
Project Speech Synthesis
Multicore Programming Primer (M-I-T) MIT Prof. Dr. Rodric Rabbah, Prof. Dr. Saman Amarasinghe Applied Sciences
3208
The Future
Multicore Programming Primer (M-I-T) MIT Prof. Dr. Rodric Rabbah, Prof. Dr. Saman Amarasinghe Applied Sciences
3209
Projects Closing
Multicore Programming Primer (M-I-T) MIT Prof. Dr. Rodric Rabbah, Prof. Dr. Saman Amarasinghe Applied Sciences
3210
The Raw Experience
Multicore Programming Primer (M-I-T) MIT Prof. Dr. Rodric Rabbah, Prof. Dr. Saman Amarasinghe Applied Sciences
3211
Projects Introduction
Multicore Programming Primer (M-I-T) MIT Prof. Dr. Rodric Rabbah, Prof. Dr. Saman Amarasinghe Applied Sciences
3212
Lecture 1 Probability Models and Axioms
Probabilistic System Analysis and Applied Probability (Fall 2010) (M-I-T) MIT Prof. Dr. John Tsitsiklis Applied Sciences
3213
Lecture 10 Continuous Bayes’ Rule; Derived Distributions
Probabilistic System Analysis and Applied Probability (Fall 2010) (M-I-T) MIT Prof. Dr. John Tsitsiklis Applied Sciences
3214
1A Overview and Introduction to Lisp
Structure and Interpretation of Computer Programs (M-I-T) MIT Harold Abelson, Gerald Jay Sussman, Julie Sussman Applied Sciences
3215
Lecture 11 Derived Distributions; Convolution; Covariance and Correlation
Probabilistic System Analysis and Applied Probability (Fall 2010) (M-I-T) MIT Prof. Dr. John Tsitsiklis Applied Sciences
3216
10A Compilation
Structure and Interpretation of Computer Programs (M-I-T) MIT Harold Abelson, Gerald Jay Sussman, Julie Sussman Applied Sciences
3217
Lecture 12 Iterated Expectations; Sum of a Random Number of Random Variables
Probabilistic System Analysis and Applied Probability (Fall 2010) (M-I-T) MIT Prof. Dr. John Tsitsiklis Applied Sciences
3218
10B Storage Allocation and Garbage Collection
Structure and Interpretation of Computer Programs (M-I-T) MIT Harold Abelson, Gerald Jay Sussman, Julie Sussman Applied Sciences
3219
Lecture 13 Bernoulli Process
Probabilistic System Analysis and Applied Probability (Fall 2010) (M-I-T) MIT Prof. Dr. John Tsitsiklis Applied Sciences
3220
1B Procedures and Processes; Substitution Model
Structure and Interpretation of Computer Programs (M-I-T) MIT Harold Abelson, Gerald Jay Sussman, Julie Sussman Applied Sciences
3221
Lecture 14 Poisson Process I
Probabilistic System Analysis and Applied Probability (Fall 2010) (M-I-T) MIT Prof. Dr. John Tsitsiklis Applied Sciences
3222
2A Higher-order Procedures
Structure and Interpretation of Computer Programs (M-I-T) MIT Harold Abelson, Gerald Jay Sussman, Julie Sussman Applied Sciences
3223
Lecture 15 Poisson Process II
Probabilistic System Analysis and Applied Probability (Fall 2010) (M-I-T) MIT Prof. Dr. John Tsitsiklis Applied Sciences
3224
2B Compound Data
Structure and Interpretation of Computer Programs (M-I-T) MIT Harold Abelson, Gerald Jay Sussman, Julie Sussman Applied Sciences
3225
Lecture 16 Markov Chains I
Probabilistic System Analysis and Applied Probability (Fall 2010) (M-I-T) MIT Prof. Dr. John Tsitsiklis Applied Sciences