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Course 6: Electrical Engineering and Computer Science
Fall 2016


Basic Undergraduate Subjects

6.00 Introduction to Computer Science and Programming
______

Undergrad (Fall, Spring) Rest Elec in Sci & Tech
Prereq: None
Units: 3-7-2
Lecture: MW3 (26-100) Lab: TBA +final
______
Introduction to computer science and programming for students with little or no programming experience. Students learn how to program and how to use computational techniques to solve problems. Topics include software design, algorithms, data analysis, and simulation techniques. Assignments are done using the Python programming language. Meets with 6.0001 first half of term and 6.0002 second half of term. Credit cannot also be received for 6.0001 or 6.0002. Final given during final exam week.
J. V. Guttag
Textbooks (Fall 2016)

6.0001 Introduction to Computer Science Programming in Python
______

Undergrad (Fall, Spring); first half of term
Prereq: None
Units: 2-3-1
Ends Oct 21. Lecture: MW3 (26-100) Recitation: F10 (36-112, 36-153) or F11 (36-112, 36-153) or F12 (36-153) or F1 (36-153) or F2 (36-153) or F3 (36-153) or F12 (36-112) or F1 (36-112) or F2 (36-112) or F3 (36-112) or F1 (36-156)
______
Introduction to computer science and programming for students with little or no programming experience. Students develop skills to program and use computational techniques to solve problems. Topics include the notion of computation, Python, simple algorithms and data structures, testing and debugging, and algorithmic complexity. Combination of 6.0001 and 6.0002 counts as REST subject. Final given in the seventh week of the term.
J. V. Guttag
Textbooks (Fall 2016)

6.0002 Introduction to Computational Thinking and Data Science
______

Undergrad (Fall, Spring); second half of term
Prereq: 6.0001 or permission of instructor
Units: 2-3-1
Begins Oct 24. Lecture: MW3 (26-100) Recitation: F10 (36-112, 36-153) or F11 (36-112, 36-153) or F12 (36-153) or F1 (36-153) or F2 (36-153) or F3 (36-153) or F12 (36-112) or F1 (36-112) or F2 (36-112) or F3 (36-112) or F1 (36-156) +final
______
Provides an introduction to using computation to understand real-world phenomena. Topics include plotting, stochastic programs, probability and statistics, random walks, Monte Carlo simulations, modeling data, optimization problems, and clustering. Combination of 6.0001 and 6.0002 counts as REST subject. Final given during final exam week.
J. V. Guttag
Textbooks (Fall 2016)

6.002 Circuits and Electronics
______

Undergrad (Fall, Spring) Rest Elec in Sci & Tech
Prereq: Physics II (GIR); Coreq: 18.03 or 2.087
Units: 4-1-7
Lecture: TR11 (34-101) Lab: TBA Recitation: WF11 (26-310) or WF12 (26-310) or WF1 (26-310) or WF2 (26-310) +final
______
Fundamentals of the lumped circuit abstraction. Resistive elements and networks, independent and dependent sources, switches and MOS devices, digital abstraction, amplifiers, and energy storage elements. Dynamics of first- and second-order networks; design in the time and frequency domains; analog and digital circuits and applications. Design exercises. Occasional laboratory.
A. Agarwal, J. del Alamo, J. H. Lang, D. J. Perreault
Textbooks (Fall 2016)

6.003 Signals and Systems
______

Undergrad (Fall, Spring) Rest Elec in Sci & Tech
Prereq: Physics II (GIR); 2.087 or 18.03
Units: 5-0-7
Lecture: TR12 (34-101) Lab: TBA Recitation: WF10 (26-210) or WF11 (26-210) or WF1 (36-144) or WF2 (36-144) +final
______
Presents the fundamentals of signal and system analysis. Topics include discrete-time and continuous-time signals, Fourier series and transforms, Laplace and Z transforms, and analysis of linear, time-invariant systems. Applications drawn broadly from engineering and physics, including audio and image processing, communications, and automatic control.
D. M. Freeman, Q. Hu, J. S. Lim
No textbook information available

6.004 Computation Structures
______

Undergrad (Fall, Spring) Rest Elec in Sci & Tech
Prereq: Physics II (GIR)
Units: 4-0-8
URL: http://6004.mit.edu/
Lecture: TR1 (10-250) Recitation: WF10 (34-301, 13-4101) or WF11 (34-301, 13-4101) or WF12 (34-303, 36-155) or WF1 (34-303, 36-155) or WF2 (34-303, 13-5101) or WF3 (34-303, 13-5101)
______
Introduces architecture of digital systems, emphasizing structural principles common to a wide range of technologies. Multilevel implementation strategies; definition of new primitives (e.g., gates, instructions, procedures, and processes) and their mechanization using lower-level elements. Analysis of potential concurrency; precedence constraints and performance measures; pipelined and multidimensional systems. Instruction set design issues; architectural support for contemporary software structures.
S. A. Ward, C. J. Terman
No required or recommended textbooks

6.005 Elements of Software Construction
______

Undergrad (Fall) Rest Elec in Sci & Tech
Prereq: 6.01; Coreq: 6.042
Units: 4-0-8
Lecture: MW1-2.30,F1 (32-123)
______
Introduces fundamental principles and techniques of software development, i.e., how to write software that is safe from bugs, easy to understand, and ready for change. Topics include specifications and invariants; testing, test-case generation, and coverage; abstract data types and representation independence; design patterns for object-oriented programming; concurrent programming, including message passing and shared concurrency, and defending against races and deadlock; and functional programming with immutable data and higher-order functions. Includes weekly programming exercises and larger group programming projects. 12 Engineering Design Points.
D. N. Jackson, R. C. Miller
No required or recommended textbooks

6.006 Introduction to Algorithms
______

Undergrad (Fall, Spring)
Prereq: 6.042; 6.01 or Coreq: 6.009
Units: 4-0-8
Lecture: TR11 (26-100) Recitation: WF10 (34-304, 34-302, 35-310) or WF11 (34-304, 34-302, 36-155) or WF12 (34-301, 34-304) or WF1 (34-304, 5-134) or WF2 (5-134, 35-310) or WF3 (35-310) or WF4 (35-310) +final
______
Introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. Emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.
R. L. Rivest, S. Devadas
Textbooks (Fall 2016)

6.007 Electromagnetic Energy: From Motors to Solar Cells
______

Undergrad (Fall) Rest Elec in Sci & Tech
Prereq: Physics II (GIR); Coreq: 2.087 or 18.03
Units: 5-1-6
Lecture: MWF1 (37-212) Lab: T EVE (7-9 PM) (38-601) or W EVE (7-9 PM) (38-601) +final
______
Discusses applications of electromagnetic and equivalent quantum mechanical principles to classical and modern devices. Covers energy conversion and power flow in both macroscopic and quantum-scale electrical and electromechanical systems, including electric motors and generators, electric circuit elements, quantum tunneling structures and instruments. Studies photons as waves and particles and their interaction with matter in optoelectronic devices, including solar cells and displays.
V. Bulovic, R. J. Ram
Textbooks (Fall 2016)

6.008 Introduction to Inference
______

Undergrad (Fall) Institute Lab
Prereq: Calculus II (GIR) or permission of instructor
Units: 4-4-4
F10-12 meets in 32-044. Lecture: MW10 (32-155) Lab: R3-5,F10-12 (35-225) Recitation: TR10 (3-442) or TR1 (34-302) or TR2 (34-302) +final
______
Introduces probabilistic modeling for problems of inference and machine learning from data, emphasizing analytical and computational aspects. Distributions, marginalization, conditioning, and structure; graphical representations. Belief propagation, decision-making, classification, estimation, and prediction. Sampling methods and analysis. Introduces asymptotic analysis and information measures. Substantial computational laboratory component explores the concepts introduced in class in the context of realistic contemporary applications. Students design inference algorithms, investigate their behavior on real data, and discuss experimental results.
P. Golland, G. W. Wornell
Textbooks (Fall 2016)

6.009 Fundamentals of Programming
(6.S04)
______

Undergrad (Fall, Spring) Institute Lab
Prereq: 6.0001
Units: 2-4-6
Lecture: T11-12.30 (54-100) Lab: F10-12 (35-225) or F1-3 (6-120) or F9-11 (3-333) or F1-3 (35-225) Recitation: W10-12 (32-124) or W1-3 (4-270) or W9-11 (35-225) or W1-3 (26-100)
______
Introduces fundamental concepts of programming. Designed to develop skills in applying basic methods from programming languages to abstract problems. Topics include programming and Python basics, computational concepts, software engineering, algorithmic techniques, data types, and recursion and tail recursion. Lab component consists of software design, construction, and implementation of design.
A. Chlipala, S. Devadas
No required or recommended textbooks

6.01 Introduction to EECS via Robot Sensing, Software and Control
______

Undergrad (Fall, Spring) Institute Lab
Prereq: 6.0001 or permission of instructor
Units: 2-4-6
URL: http://mit.edu/6.01/index.html
Lecture: T9.30-11 (4-270) Lab: T11-12.30,R2-5 (34-501) or T2-3.30,R9.30-12.30 (34-501) +final
______
An integrated introduction to electrical engineering and computer science, taught using substantial laboratory experiments with mobile robots. Key issues in the design of engineered artifacts operating in the natural world: measuring and modeling system behaviors; assessing errors in sensors and effectors; specifying tasks; designing solutions based on analytical and computational models; planning, executing, and evaluating experimental tests of performance; refining models and designs. Issues addressed in the context of computer programs, control systems, probabilistic inference problems, circuits and transducers, which all play important roles in achieving robust operation of a large variety of engineered systems.
D. M. Freeman, A. Hartz, L. P. Kaelbling, T. Lozano-Perez
No required or recommended textbooks

6.011 Signals, Systems and Inference
______

Undergrad (Spring)
Prereq: 6.003; 6.008, 6.041A, or 18.600
Units: 4-0-8
______
Covers signals, systems and inference in communication, control and signal processing. Topics include input-output and state-space models of linear systems driven by deterministic and random signals; time- and transform-domain representations in discrete and continuous time; and group delay. State feedback and observers. Probabilistic models; stochastic processes, correlation functions, power spectra, spectral factorization. Least-mean square error estimation; Wiener filtering. Hypothesis testing; detection; matched filters.
A. V. Oppenheim, G. C. Verghese

6.012 Microelectronic Devices and Circuits
______

Undergrad (Fall, Spring)
Prereq: 6.002
Units: 4-0-8
Lecture: TR11 (32-141) Recitation: WF1 (34-302) or WF2 (34-302) +final
______
Microelectronic device modeling, and basic microelectronic circuit analysis and design. Physical electronics of semiconductor junction and MOS devices. Relating terminal behavior to internal physical processes, developing circuit models, and understanding the uses and limitations of different models. Use of incremental and large-signal techniques to analyze and design transistor circuits, with examples chosen from digital circuits, linear amplifiers, and other integrated circuits. Design project.
A. I. Akinwande, D. A. Antoniadis, J. Kong, C. G. Sodini
Textbooks (Fall 2016)

6.013 Electromagnetics and Applications
______

Undergrad (Spring)
Prereq: Calculus II (GIR), Physics II (GIR)
Units: 3-3-6
______
Analysis and design of modern applications that employ electromagnetic phenomena for signals and power transmission in RF, microwaves, optical and wireless communication systems. Fundamentals include dynamic solutions for Maxwell's equations; electromagnetic power and energy, waves in media, guided waves, radiation, and diffraction; coupling to media and structures; resonance & filters; acoustic analogs. Labs include student hands-on activities from building to testing of devices and systems (e.g. radar) that reinforce lectures, with a focus on fostering creativity and debugging skills. 6.002 and 6.007 are recommended but not required.
L. Daniel, M. R. Watts

6.02 Introduction to EECS via Communications Networks
______

Undergrad (Fall) Institute Lab
Prereq: 6.0001
Units: 4-4-4
Lecture: MW2 (34-101) Recitation: TR10 (34-304) or TR11 (34-304) or TR12 (34-304) or TR1 (34-304) or TR2 (34-301) or TR3 (34-301) or TR10 (24-112) or TR11 (26-210) +final
______
Studies key concepts, systems, and algorithms to reliably communicate data in settings ranging from the cellular phone network and the Internet to deep space. Weekly laboratory experiments explore these areas in depth. Topics presented in three modules - bits, signals, and packets - spanning the multiple layers of a communication system. Bits module includes information, entropy, data compression algorithms, and error correction with block and convolutional codes. Signals module includes modeling physical channels and noise, signal design, filtering and detection, modulation, and frequency-division multiplexing. Packets module includes switching and queuing principles, media access control, routing protocols, and data transport protocols.
H. Balakrishnan, K. LaCurts, G. C. Verghese,
No required or recommended textbooks

6.021[J] Cellular Neurophysiology
______

Undergrad (Fall)
(Same subject as 2.791[J], 20.370[J])
(Subject meets with 2.794[J], 6.521[J], 20.470[J], HST.541[J])
Prereq: Physics II (GIR); 18.03; 2.005, 6.002, 6.003, 6.071, 10.301, 20.110, or permission of instructor
Units: 5-2-5
Lecture: MWF10 (32-144) Lab: TBA Recitation: T12 (34-303) or T4 (34-302) +final
______
Integrated overview of the biophysics of cells from prokaryotes to neurons, with a focus on mass transport and electrical signal generation across cell membrane. First half of course focuses on mass transport through membranes: diffusion, osmosis, chemically mediated, and active transport. Second half focuses on electrical properties of cells: ion transport to action potentials in electrically excitable cells. Synaptic transmission. Electrical properties interpreted via kinetic and molecular properties of single voltage-gated ion channels. Laboratory and computer exercises illustrate the concepts. Students taking graduate version complete different assignments. Preference to juniors and seniors.
J. Han, T. Heldt, J. Voldman
Textbooks (Fall 2016)

6.022[J] Quantitative Systems Physiology
______

Undergrad (Spring)
(Same subject as 2.792[J], HST.542[J])
(Subject meets with 2.796[J], 6.522[J])
Prereq: Physics II (GIR), 18.03, or permission of instructor
Units: 4-2-6
URL: http://web.mit.edu/6.022j/www/
______
Application of the principles of energy and mass flow to major human organ systems. Mechanisms of regulation and homeostasis. Anatomical, physiological and pathophysiological features of the cardiovascular, respiratory and renal systems. Systems, features and devices that are most illuminated by the methods of physical sciences. Laboratory work includes some animal studies. Students taking graduate version complete additional assignments. 2 Engineering Design Points.
T. Heldt, R. G. Mark, C. M. Stultz

6.023[J] Fields, Forces and Flows in Biological Systems
______

Undergrad (Spring)
(Same subject as 2.793[J], 20.330[J])
Prereq: Physics II (GIR); 2.005, 6.021, or permission of instructor, Coreq: 20.309
Units: 4-0-8
______
Introduction to electric fields, fluid flows, transport phenomena and their application to biological systems. Flux and continuity laws, Maxwell's equations, electro-quasistatics, electro-chemical-mechanical driving forces, conservation of mass and momentum, Navier-Stokes flows, and electrokinetics. Applications include biomolecular transport in tissues, electrophoresis, and microfluidics.
J. Han, S. Manalis

6.024[J] Molecular, Cellular, and Tissue Biomechanics
______

Not offered academic year 2016-2017Undergrad (Spring)
(Same subject as 2.797[J], 3.053[J], 20.310[J])
Prereq: 2.370 or 2.772J; 18.03 or 3.016; Biology (GIR)
Units: 4-0-8
______
Develops and applies scaling laws and the methods of continuum mechanics to biomechanical phenomena over a range of length scales. Topics include structure of tissues and the molecular basis for macroscopic properties; chemical and electrical effects on mechanical behavior; cell mechanics, motility and adhesion; biomembranes; biomolecular mechanics and molecular motors. Experimental methods for probing structures at the tissue, cellular, and molecular levels.
R. D. Kamm, A. J. Grodzinsky, K. Van Vliet

6.025[J] Medical Device Design
______

Undergrad (Fall)
(Same subject as 2.750[J])
(Subject meets with 2.75[J], 6.525[J], HST.552[J])
Prereq: 2.70, 2.72, 2.678, 6.115, 22.071, or permission of instructor
Units: 3-0-9
URL: http://web.mit.edu/2.75/
Lecture: MW1-2.30 (3-270)
______
Application of mechanical and electrical engineering fundamentals to the design of medical devices that address clinical needs. Throughout the term, students work in small teams on a major project to translate a clinical challenge into a proof-of-concept prototype device. Students conduct user analysis, develop design specifications, and follow a structured process to cultivate creative designs and apply analytical techniques to optimize them. They deepen their understanding of art and intellectual property by researching prior representations. Develops practical skills in prototyping and testing as well as project management. Includes lectures, problem sets and exams that focus on design fundamentals. Instruction and practice in written and oral communication provided. Students taking graduate version complete additional assignments. Enrollment limited.
A. H. Slocum, G. Hom
No required or recommended textbooks

6.027[J] Biomolecular Feedback Systems
______

Undergrad (Spring)
(Same subject as 2.180[J])
(Subject meets with 2.18[J], 6.557[J])
Prereq: 18.03, Biology (GIR), or permission of instructor
Units: 3-0-9
______
Comprehensive introduction to dynamics and control of biomolecular systems with emphasis on design/analysis techniques from control theory. Provides a review of biology concepts, regulation mechanisms, and models. Covers basic enabling technologies, engineering principles for designing biological functions, modular design techniques, and design limitations. Students taking graduate version complete additional assignments.
D. Del Vecchio

6.03 Introduction to EECS via Medical Technology
______

Undergrad (Spring) Institute Lab
Prereq: Calculus II (GIR), Physics II (GIR)
Units: 4-4-4
______
Explores biomedical signals generated from electrocardiograms, glucose detectors or ultrasound images, and magnetic resonance images. Topics include physical characterization and modeling of systems in the time and frequency domains; analog and digital signals and noise; basic machine learning including decision trees, clustering, and classification; and introductory machine vision. Labs designed to strengthen background in signal processing and machine learning. Students design and run structured experiments, and develop and test procedures through further experimentation.
C. M. Stultz, E. Adalsteinsson

6.031 Elements of Software Construction
(New)
______

Undergrad (Spring)
Prereq: 6.009
Units: 5-0-10
______
Introduces fundamental principles and techniques of software development: how to write software that is safe from bugs, easy to understand, and ready for change. Topics include specifications and invariants; testing, test-case generation, and coverage; abstract data types and representation independence; design patterns for object-oriented programming; concurrent programming, including message passing and shared concurrency, and defending against races and deadlock; and functional programming with immutable data and higher-order functions. Includes weekly programming exercises and larger group programming projects.
M. Goldman, R. C. Miller

6.033 Computer System Engineering
______

Undergrad (Spring)
Prereq: 6.004; 6.005 or 6.009
Units: 5-1-6
URL: http://web.mit.edu/6.033/www/
______
Topics on the engineering of computer software and hardware systems: techniques for controlling complexity; strong modularity using client-server design, operating systems; performance, networks; naming; security and privacy; fault-tolerant systems, atomicity and coordination of concurrent activities, and recovery; impact of computer systems on society. Case studies of working systems and readings from the current literature provide comparisons and contrasts. Includes a single, semester-long design project. Students engage in extensive written communication exercises. Enrollment may be limited.
K. LaCurts, M. F. Kaashoek, H. Balakrishnan

6.034 Artificial Intelligence
______

Undergrad (Fall)
Prereq: 6.0001
Units: 4-3-5
URL: http://courses.csail.mit.edu/6.034/
Lecture: MWF10 (10-250) Recitation: M11 (26-302, 34-301, 34-302, 34-304) or M12 (34-302) or M11 (36-372) or M12 (34-304) or M1 (34-303, 34-304) or M2 (34-301, 34-304) or M3 (34-304) or M11 (38-166) or T10 (34-301, 34-302) or T11 (34-301) or T12 (26-328, 34-301) or T1 (34-301, 34-303) or T2 (34-303) or T3 (34-303) or M12 (38-166, 26-302) or T11 (26-302) +final
______
Introduces representations, methods, and architectures used to build applications and to account for human intelligence from a computational point of view. Covers applications of rule chaining, constraint propagation, constrained search, inheritance, statistical inference, and other problem-solving paradigms. Also addresses applications of identification trees, neural nets, genetic algorithms, support-vector machines, boosting, and other learning paradigms. Considers what separates human intelligence from that of other animals.
P. H. Winston
No textbook information available

6.035 Computer Language Engineering
______

Undergrad (Fall)
Prereq: 6.004; 6.005 or 6.031
Units: 4-4-4
URL: http://web.mit.edu/6.035/6035.html
Lecture: MWF11 (3-370) Recitation: TR11 (4-149)
______
Analyzes issues associated with the implementation of higher-level programming languages. Fundamental concepts, functions, and structures of compilers. The interaction of theory and practice. Using tools in building software. Includes a multi-person project on compiler design and implementation.
M. C. Rinard
No textbook information available

6.036 Introduction to Machine Learning
______

Undergrad (Spring)
(Subject meets with 6.862)
Prereq: 6.0001
Units: 4-0-8
______
Introduces principles, algorithms, and applications of machine learning from the point of view of modeling and prediction; formulation of learning problems; representation, over-fitting, generalization; clustering, classification, probabilistic modeling; and methods such as support vector machines, hidden Markov models, and Bayesian networks. Students taking graduate version complete additional assignments.
R. Barzilay, T. Jaakkola, L. P. Kaelbling

6.037 Structure and Interpretation of Computer Programs
______

Undergrad (IAP)
Prereq: None
Units: 1-0-5 [P/D/F]
______
Studies the structure and interpretation of computer programs which transcend specific programming languages. Demonstrates thought patterns for computer science using Scheme. Includes weekly programming projects. Enrollment may be limited.
Staff

6.041A Introduction to Probability I
(New)
______

Undergrad (Fall, Spring); first half of term
(Subject meets with 6.431A)
Prereq: Calculus II (GIR)
Units: 2-0-4
Ends Oct 21. Lecture: MW12 (34-101) Recitation: TR11 (24-121) or TR12 (24-121) or TR1 (24-121) or TR2 (24-121)
______
Provides an introduction to probability theory and the modeling and analysis of probabilistic systems. Probabilistic models, conditional probability. Discrete and continuous random variables. Expectation and conditional expectation. Limit Theorems. Students taking graduate version complete additional assignments. Combination of 6.041A and 6.041B counts as a REST subject.
P. Jaillet, J. N. Tsitsiklis
No textbook information available

6.041B Introduction to Probability II
(New)
______

Undergrad (Fall, Spring); second half of term
(Subject meets with 6.431B)
Prereq: 6.041A
Units: 2-0-4
Begins Oct 24. Lecture: MW12 (34-101) Recitation: TR11 (24-121) or TR12 (24-121) or TR1 (24-121) or TR2 (24-121) +final
______
Building on 6.041A, further discusses topics in probability. Bayesian estimation and hypothesis testing. Elements of statistical inference. Bernoulli and Poisson processes. Markov chains. Students taking graduate version complete additional assignments. Combination of 6.041A and 6.041B counts as a REST subject.
P. Jaillet, J. N. Tsitsiklis
No textbook information available

6.042[J] Mathematics for Computer Science
______

Undergrad (Fall, Spring) Rest Elec in Sci & Tech
(Same subject as 18.062[J])
Prereq: Calculus I (GIR)
Units: 5-0-7
URL: http://theory.csail.mit.edu/classes/6.042
Lecture: TR2.30-4 (26-100) Recitation: WF9 (38-166) or WF10 (38-166) or WF11 (38-166) or WF12 (38-166) or WF1 (38-166) or WF2 (38-166) or WF3 (38-166) or WF4 (38-166) or WF10 (13-3101) or WF11 (13-3101) or WF12 (13-3101) or WF1 (13-3101) or WF2 (13-3101) or WF3 (13-3101) or WF4 (13-3101) or WF10 (26-168) or WF11 (26-168) or WF12 (26-168) or WF1 (26-168) or WF2 (26-168) or WF3 (26-168) or WF4 (26-168) or WF11 (24-112) or WF12 (24-112) or WF1 (24-112) or WF9 (26-168) +final
______
Elementary discrete mathematics for computer science and engineering. Emphasis on mathematical definitions and proofs as well as on applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics include recursive definition and structural induction, state machines and invariants, integer congruences, recurrences, generating functions.
F. T. Leighton, A. R. Meyer, A. Moitra
No required or recommended textbooks

6.045[J] Automata, Computability, and Complexity
______

Undergrad (Spring)
(Same subject as 18.400[J])
Prereq: 6.042
Units: 4-0-8
URL: http://math.mit.edu/classes/18.400
______
Provides an introduction to some of the central ideas of theoretical computer science, including circuits, finite automata, Turing machines and computability, efficient algorithms and reducibility, the P versus NP problem, NP-completeness, the power of randomness, cryptography, computational learning theory, and quantum computing. Examines the classes of problems that can and cannot be solved in various computational models.
S. Aaronson

6.046[J] Design and Analysis of Algorithms
______

Undergrad (Fall, Spring)
(Same subject as 18.410[J])
Prereq: 6.006
Units: 4-0-8
URL: http://math.mit.edu/classes/18.410
Lecture: TR11-12.30 (32-123) Recitation: F10 (4-159) or F11 (4-159, 4-149, 36-156) or F12 (36-156, 4-159) or F1 (4-159, 4-149) or F2 (35-308) or F3 (35-308) +final
______
Techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics include sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; greedy algorithms; amortized analysis; graph algorithms; and shortest paths. Advanced topics may include network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.
E. Demaine, M. Goemans
Textbooks (Fall 2016)

6.047 Computational Biology: Genomes, Networks, Evolution
______

Undergrad (Fall)
(Subject meets with 6.878[J], HST.507[J])
Prereq: 6.006, 6.041B, Biology (GIR); or permission of instructor
Units: 3-0-9
Lecture: TR1-2.30 (32-141) Recitation: F3 (4-237)
______
Covers the algorithmic and machine learning foundations of computational biology, combining theory with practice. Principles of algorithm design, influential problems and techniques, and analysis of large-scale biological datasets. Topics include (a) genomes: sequence analysis, gene finding, RNA folding, genome alignment and assembly, database search; (b) networks: gene expression analysis, regulatory motifs, biological network analysis; (c) evolution: comparative genomics, phylogenetics, genome duplication, genome rearrangements, evolutionary theory. These are coupled with fundamental algorithmic techniques including: dynamic programming, hashing, Gibbs sampling, expectation maximization, hidden Markov models, stochastic context-free grammars, graph clustering, dimensionality reduction, Bayesian networks.
M. Kellis
No textbook information available

6.049[J] Evolutionary Biology: Concepts, Models and Computation
______

Undergrad (Spring)
(Same subject as 7.33[J])
Prereq: 7.03; 6.0001 or permission of instructor
Units: 3-0-9
______
Explores and illustrates how evolution explains biology, with an emphasis on computational model building for analyzing evolutionary data. Covers key concepts of biological evolution, including adaptive evolution, neutral evolution, evolution of sex, genomic conflict, speciation, phylogeny and comparative methods, life's history, coevolution, human evolution, and evolution of disease.
R. Berwick, D. Bartel

6.050[J] Information, Entropy, and Computation
______

Undergrad (Spring)
(Same subject as 2.110[J])
Prereq: Physics I (GIR)
Units: 3-0-6
______
Explores the ultimate limits to communication and computation, with an emphasis on the physical nature of information and information processing. Topics include information and computation, digital signals, codes, and compression. Biological representations of information. Logic circuits, computer architectures, and algorithmic information. Noise, probability, and error correction. The concept of entropy applied to channel capacity and to the second law of thermodynamics. Reversible and irreversible operations and the physics of computation. Quantum computation.
P. Penfield, Jr., S. Lloyd

6.057 Introduction to MATLAB
______

Undergrad (IAP)
Prereq: None
Units: 1-0-2 [P/D/F]
______
Accelerated introduction to MATLAB and its popular toolboxes. Lectures are interactive, with students conducting sample MATLAB problems in real time. Includes problem-based MATLAB assignments. Students must provide their own laptop and software. Enrollment limited.
Staff

6.058 Introduction to Signals and Systems, and Feedback Control
______

Undergrad (IAP)
Prereq: Calculus II (GIR) or permission of instructor
Units: 2-2-2 [P/D/F]
______
Introduces fundamental concepts for 6.003, including Fourier and Laplace transforms, convolution, sampling, filters, feedback control, stability, and Bode plots. Students engage in problem solving, using Mathematica and MATLAB software extensively to help visualize processing in the time frequency domains.
Staff

6.061 Introduction to Electric Power Systems
______

Not offered academic year 2017-2018Undergrad (Spring)
(Subject meets with 6.690)
Prereq: 6.002, 6.013
Units: 3-0-9
______
Electric circuit theory with application to power handling electric circuits. Modeling and behavior of electromechanical devices, including magnetic circuits, motors, and generators. Operational fundamentals of synchronous, induction and DC machinery. Interconnection of generators and motors with electric power transmission and distribution circuits. Power generation, including alternative and sustainable sources. Students taking graduate version complete additional assignments.
J. L. Kirtley, Jr.

6.07[J] Projects in Microscale Engineering for the Life Sciences
______

Undergrad (Spring)
Not offered regularly; consult department
(Same subject as HST.410[J])
Prereq: None
Units: 2-4-3
______
A project-based introduction to manipulating and characterizing cells and biological molecules using microfabricated tools. In the first half of the term, students perform laboratory exercises designed to introduce the design, manufacture, and use of microfluidic channels; techniques for sorting and manipulating cells and biomolecules; and making quantitative measurements using optical detection and fluorescent labeling. In the second half of the term, students work in small groups to design and test a microfluidic device to solve a real-world problem of their choosing. Includes exercises in written and oral communication and team building. Limited to 20; preference to freshmen.
D. Freeman, M. Gray

6.070[J] Electronics Project Laboratory
______

Undergrad (Fall, Spring)
(Same subject as EC.120[J])
Prereq: None
Units: 2-2-2
Lecture: M EVE (7-10 PM) (4-409)
______
Intuition-based introduction to electronics, electronic components and test equipment such as oscilloscopes, meters (voltage, resistance inductance, capacitance, etc.), and signal generators. Emphasizes individual instruction and development of skills, such as soldering, assembly, and troubleshooting. Students design, build, and keep a small electronics project to put their new knowledge into practice. Intended for students with little or no previous background in electronics. Enrollment may be limited.
J. Bales
No required or recommended textbooks

6.072[J] Introduction to Digital Electronics
______

Undergrad (Fall, Spring)
(Same subject as EC.110[J])
Prereq: None
Units: 0-3-3 [P/D/F]
Lecture: M EVE (7-10 PM) (4-402)
______
Design your own circuits for times when off-the-shelf solutions are not available. Seminar begins with assembly of a utility board. Weekly labs cover digital logic gates, memory elements, and finite-state machine design. Seminar concludes with a team-based design project. Preference given to freshmen. Maximum of 10 students per term, lottery at the first class session if oversubscribed .
J. Bales
No required or recommended textbooks

6.073[J] Creating Video Games
______

Undergrad (Spring) HASS Arts
(Same subject as CMS.611[J])
Prereq: 6.01, CMS.301, or CMS.608
Units: 3-3-6
______
Introduces students to the complexities of working in small, multidisciplinary teams to develop video games. Covers creative design and production methods, stressing design iteration and regular testing across all aspects of game development (design, visual arts, music, fiction, and programming). Assumes a familiarity with current video games, and the ability to discuss games critically. Previous experience in audio design, visual arts, or project management recommended. Limited to 24.
P. Tan, S. Verrilli, R. Eberhardt

6.S062 Special Subject in Electrical Engineering and Computer Science
______

Undergrad (Fall) Can be repeated for credit
Prereq: None
Units arranged
URL: http://www.eecs.mit.edu/academics-admissions/academic-information/subject-updates-st-2016
Lecture: M3-5 (36-153)
______
Basic undergraduate subjects not offered in the regular curriculum.
Consult Department
No textbook information available

6.S063, 6.S064 Special Subject in Electrical Engineering and Computer Science
______

Undergrad (Fall) Can be repeated for credit
Prereq: None
Units arranged
6.S064: URL: https://www.eecs.mit.edu/academics-admissions/academic-information/subject-updates-ft-2016/6s064
6.S063: TBA.
6.S064: Lecture: TR11 (34-101) +final
______
Basic undergraduate subjects not offered in the regular curriculum.
Consult Department
6.S063: No textbook information available
6.S064: No textbook information available

6.S08 Special Subject: Interconnected Embedded Systems
______

Undergrad (Spring) Institute Lab
Prereq: None
Units: 1-5-6
______
Introduction to embedded systems in the context of connected devices, wearables and the "Internet of Things". Topics include microcontrollers, energy utilization, algorithmic efficiency, interfacing with sensors, networking, cryptography, local versus distributed computation, data analytics, and 3D printing. Students will design, make, and program an internet-connected wearable device. Final project where student teams will design and demo their own cloud-connected wearable system. Licensed for Spring 2016 by the Committee on Curricula. Enrollment limited; preference to first- and second-year students.
J. Voldman, J. D. Steinmeyer

6.S076-6.S084 Special Subject in Electrical Engineering and Computer Science
______

Undergrad (Fall) Can be repeated for credit
Prereq: Permission of instructor
Units arranged
6.S082: URL: http://www.eecs.mit.edu/academics-admissions/academic-information/subject-updates-ft-2016
6.S080: TBA.
6.S084: Lecture: MW1-2.30 (1-150)
______
Covers subject matter not offered in the regular curriculum. Consult department to learn of offerings for a particular term.
Consult Department
6.S080: No required or recommended textbooks
6.S084: No textbook information available

6.S085-6.S099 Special Subject in Electrical Engineering and Computer Science
______

Undergrad (IAP, Spring) Can be repeated for credit
Not offered regularly; consult department
Prereq: Permission of instructor
Units arranged [P/D/F]
______
Covers subject matter not offered in the regular curriculum. Consult department to learn of offerings for a particular term.
Consult Department

Undergraduate Laboratory Subjects

6.100 Electrical Engineering and Computer Science Project
______

Undergrad (Fall, Spring, Summer) Can be repeated for credit
Prereq: None
Units arranged
TBA.
______
Individual experimental work related to electrical engineering and computer science. Student must make arrangements with a project supervisor and file a proposal endorsed by the supervisor. Departmental approval required. Written report to be submitted upon completion of work.
Consult Department Undergraduate Office
No textbook information available (Summer 2016); No required or recommended textbooks (Fall 2016)

6.101 Introductory Analog Electronics Laboratory
______

Undergrad (Spring) Institute Lab
Prereq: 6.002 or 6.071
Units: 2-9-1
URL: http://web.mit.edu/6.101/www/
______
Introductory experimental laboratory explores the design, construction, and debugging of analog electronic circuits. Lectures and laboratory projects in the first half of the course investigate the performance characteristics of semiconductor devices (diodes, BJTs, and MOSFETs) and functional analog building blocks, including single-stage amplifiers, op amps, small audio amplifier, filters, converters, sensor circuits, and medical electronics (ECG, pulse-oximetry). Projects involve design, implementation, and presentation in an environment similar to that of industry engineering design teams. Instruction and practice in written and oral communication provided. Opportunity to simulate real-world problems and solutions that involve tradeoffs and the use of engineering judgment. Engineers from local companies help students with their design projects.
G. Hom

6.111 Introductory Digital Systems Laboratory
______

Undergrad (Fall) Institute Lab
Prereq: 6.002, 6.071, or 16.004
Units: 3-7-2
Lecture: TR2.30-4 (32-124) Lab: TBA
______
Lectures and labs on digital logic, flip flops, PALs, FPGAs, counters, timing, synchronization, and finite-state machines prepare students for the design and implementation of a final project of their choice: games, music, digital filters, wireless communications, video, or graphics. Extensive use of Verilog for describing and implementing digital logic designs.
A. P. Chandrakasan, G. P. Hom
No required or recommended textbooks

6.115 Microcomputer Project Laboratory
______

Undergrad (Spring) Institute Lab
(Subject meets with 6.1151)
Prereq: 6.002, 6.003, 6.004, or 6.007
Units: 3-6-3
______
Introduces analysis and design of embedded systems. Microcontrollers provide adaptation, flexibility, and real-time control. Emphasizes construction of complete systems, including a five-axis robot arm, a fluorescent lamp ballast, a tomographic imaging station (e.g., a CAT scan), and a simple calculator. Presents a wide range of basic tools, including software and development tools, programmable system on chip, peripheral components such as A/D converters, communication schemes, signal processing techniques, closed-loop digital feedback control, interface and power electronics, and modeling of electromechanical systems. Includes a sequence of assigned projects, followed by a final project of the student's choice, emphasizing creativity and uniqueness. Provides instruction in written and oral communication. Students taking independent inquiry version 6.1151 expand the scope of their laboratory project.
S. B. Leeb

6.1151 Microcomputer Project Laboratory - Independent Inquiry
(New)
______

Undergrad (Spring)
(Subject meets with 6.115)
Prereq: 6.002, 6.003, 6.004, or 6.007
Units: 3-9-3
______
Introduces analysis and design of embedded systems. Microcontrollers provide adaptation, flexibility, and real-time control. Emphasizes construction of complete systems, including a five-axis robot arm, a fluorescent lamp ballast, a tomographic imaging station (e.g., a CAT scan), and a simple calculator. Presents a wide range of basic tools, including software and development tools, programmable system on chip, peripheral components such as A/D converters, communication schemes, signal processing techniques, closed-loop digital feedback control, interface and power electronics, and modeling of electromechanical systems. Includes a sequence of assigned projects, followed by a final project of the student's choice, emphasizing creativity and uniqueness. Provides instruction in written and oral communication. Students taking independent inquiry version 6.1151 expand the scope of their laboratory project.
S. B. Leeb

6.117 Introduction to Electrical Engineering Lab Skills
______

Undergrad (IAP)
Prereq: None
Units: 1-3-2 [P/D/F]
______
Introduces basic electrical engineering concepts, components, and laboratory techniques. Covers analog integrated circuits, power supplies, and digital circuits. Lab exercises provide practical experience in constructing projects using multi-meters, oscilloscopes, logic analyzers, and other tools. Includes a project in which students build a circuit to display their own EKG. Enrollment limited.
G. P. Hom

6.123[J] Bioinstrumentation Project Lab
______

Undergrad (Spring)
(Same subject as 20.345[J])
Prereq: Biology (GIR), and 2.004 or 6.003; or 20.309; or permission of instructor
Units: 2-7-3
______
In-depth examination of instrumentation design, principles and techniques for studying biological systems, from single molecules to entire organisms. Lectures cover optics, advanced microscopy techniques, electronics for biological measurement, magnetic resonance imaging, computed tomography, MEMs, microfluidic devices, and limits of detection. Students select two lab exercises during the first half of the semester and complete a final design project in the second half. Lab emphasizes design process and skillful realization of a robust system. Enrollment limited; preference to Course 20 majors and minors.
E. Boyden, M. Jonas, S. F. Nagle, P. So, S. Wasserman, M. F. Yanik

6.129[J] Biological Circuit Engineering Laboratory
______

Undergrad (Spring) Institute Lab
(Same subject as 20.129[J])
Prereq: Biology (GIR), Calculus II (GIR)
Units: 2-8-2
______
Students assemble individual genes and regulatory elements into larger-scale circuits; they experimentally characterize these circuits in yeast cells using quantitative techniques, including flow cytometry, and model their results computationally. Emphasizes concepts and techniques to perform independent experimental and computational synthetic biology research. Discusses current literature and ongoing research in the field of synthetic biology. Instruction and practice in oral and written communication provided. Enrollment limited.
T. Lu, R. Weiss

6.131 Power Electronics Laboratory
______

Undergrad (Fall) Institute Lab
(Subject meets with 6.1311)
Prereq: 6.002, 6.003, or 6.007
Units: 3-6-3
Lecture: TR1 (34-101) Lab: W3 (34-101)
______
Introduces the design and construction of power electronic circuits and motor drives. Laboratory exercises include the construction of drive circuitry for an electric go-cart, flash strobes, computer power supplies, three-phase inverters for AC motors, and resonant drives for lamp ballasts and induction heating. Basic electric machines introduced include DC, induction, and permanent magnet motors, with drive considerations. Provides instruction in written and oral communication. Students taking independent inquiry version 6.1131 expand the scope of their laboratory project.
S. B. Leeb
Textbooks (Fall 2016)

6.1311 Power Electronics Laboratory - Independent Inquiry
(New)
______

Undergrad (Fall)
(Subject meets with 6.131)
Prereq: 6.002, 6.003, or 6.007
Units: 3-9-3
Lecture: TR1 (34-101) Lab: W3 (34-101)
______
Introduces the design and construction of power electronic circuits and motor drives. Laboratory exercises include the construction of drive circuitry for an electric go-cart, flash strobes, computer power supplies, three-phase inverters for AC motors, and resonant drives for lamp ballasts and induction heating. Basic electric machines introduced include DC, induction, and permanent magnet motors, with drive considerations. Provides instruction in written and oral communication. Students taking independent inquiry version 6.1131 expand the scope of their laboratory project.
S. B. Leeb
Textbooks (Fall 2016)

6.141[J] Robotics: Science and Systems
______

Undergrad (Spring) Institute Lab
(Same subject as 16.405[J])
Prereq: 1.00 or 6.0001; 2.003, 6.005, 6.006, 6.009, or 16.06; or permission of instructor
Units: 2-6-4
URL: http://courses.csail.mit.edu/rss/
______
Presents concepts, principles, and algorithms for sensing and computation related to the physical world. Topics include motion planning, geometric reasoning, kinematics and dynamics, state estimation, tracking, map building, manipulation, human-robot interaction, fault diagnosis, and embedded system development. Students specify and design a small-scale yet complex robot capable of real-time interaction with the natural world. Students engage in extensive written and oral communication exercises. Enrollment limited.
S. Karaman, D. Rus

6.146 Mobile Autonomous Systems Laboratory: MASLAB
______

Undergrad (IAP) Can be repeated for credit
Prereq: None
Units: 2-2-2 [P/D/F]
______
Autonomous robotics contest emphasizing technical AI, vision, mapping and navigation from a robot-mounted camera. Few restrictions are placed on materials, sensors, and/or actuators enabling teams to build robots very creatively. Teams should have members with varying engineering, programming and mechanical backgrounds. Culminates with a robot competition at the end of IAP. Enrollment limited.
Staff

6.147 The Battlecode Programming Competition
______

Undergrad (IAP) Can be repeated for credit
Prereq: None
Units: 2-0-4 [P/D/F]
URL: http://www.battlecode.org
______
Artificial Intelligence programming contest in Java. Student teams program virtual robots to play Battlecode, a real-time strategy game. Competition culminates in a live BattleCode tournament. Assumes basic knowledge of programming.
Staff

6.148 Web Programming Competition
______

Undergrad (IAP) Can be repeated for credit
Prereq: Permission of instructor
Units: 1-0-5 [P/D/F]
______
Teams compete to build the most functional and user-friendly website. Competition is judged by industry experts and includes novice and advanced divisions. Prizes awarded. Lectures and workshops cover website basics. Enrollment limited.
Staff

6.149 Introduction to Programming Using Python
______

Not offered academic year 2016-2017Undergrad (IAP)
Prereq: None
Units: 3-0-3 [P/D/F]
______
Fact-paced introduction to Python programming language for students with little or no programming experience. Covers both function and object-oriented concepts. Includes weekly lab exercises and final project. Enrollment limited.
Staff

6.150 Mobile Applications Competition
______

Undergrad (IAP) Can be repeated for credit
Not offered regularly; consult department
Prereq: Permission of instructor
Units: 2-2-2 [P/D/F]
______
Student teams design and build an Android application based on a given theme. Lectures and labs led by experienced students and leading industry experts, covering the basics of Android development, concepts and tools to help participants build great apps. Contest culminates with a public presentation in front of a judging panel comprised of professional developers and MIT faculty. Prizes awarded. Enrollment limited.
Staff

6.151 iOS Game Design and Development Competition
______

Undergrad (IAP)
Prereq: None
Units: 2-2-2 [P/D/F]
______
Introduction to iOS game design and development for students already familiar with object-oriented programming. Provides a set of basic tools (Objective-C and Cocos2D) and exposure to real-world issues in game design. Working in small teams, students complete a final project in which they create their own iPhone game. At the end of IAP, teams present their games in competition for prizes awarded by a judging panel of gaming experts.
Staff

6.152[J] Micro/Nano Processing Technology
______

Undergrad (Fall)
(Same subject as 3.155[J])
Prereq: Permission of instructor
Units: 3-4-5
Lecture: MW2.30-4 (32-124)
______
Introduces the theory and technology of micro/nano fabrication. Lectures and laboratory sessions on basic processing techniques such as vacuum processes, lithography, diffusion, oxidation, and pattern transfer. Students fabricate MOS capacitors, nanomechanical cantilevers, and microfluidic mixers. Emphasis on the interrelationships between material properties and processing, device structure, and the electrical, mechanical, optical, chemical or biological behavior of devices. Provides background for thesis work in micro/nano fabrication. Students engage in extensive written and oral communication exercises.
L. F. Velasquez-Garcia, J. Michel
Textbooks (Fall 2016)

6.161 Modern Optics Project Laboratory
______

Undergrad (Fall) Institute Lab
(Subject meets with 6.637)
Prereq: 6.003
Units: 3-5-4
URL: http://web.mit.edu/6.161/www/index.html
Lecture: TR2.30-4 (34-304) Lab: TBA
______
Lectures, laboratory exercises and projects on optical signal generation, transmission, detection, storage, processing and display. Topics include polarization properties of light; reflection and refraction; coherence and interference; Fraunhofer and Fresnel diffraction; holography; Fourier optics; coherent and incoherent imaging and signal processing systems; optical properties of materials; lasers and LEDs; electro-optic and acousto-optic light modulators; photorefractive and liquid-crystal light modulation; display technologies; optical waveguides and fiber-optic communication systems; photodetectors. Students may use this subject to find an advanced undergraduate project. Students engage in extensive oral and written communcation exercises. Recommended prerequisites: 6.007 or 8.03.
C. Warde
No textbook information available

6.163 Strobe Project Laboratory
______

Undergrad (Fall, Spring) Institute Lab
Prereq: Physics II (GIR) or permission of instructor
Units: 2-8-2
Lecture: MW12 (4-149) Lab: TBA
______
Application of electronic flash sources to measurement and photography. First half covers fundamentals of photography and electronic flashes, including experiments on application of electronic flash to photography, stroboscopy, motion analysis, and high-speed videography. Students write four extensive lab reports. In the second half, students work in small groups to select, design, and execute independent projects in measurement or photography that apply learned techniques. Project planning and execution skills are discussed and developed over the term. Students engage in extensive written and oral communication exercises. Enrollment limited.
J. K. Vandiver, J. W. Bales
No required or recommended textbooks

6.169 Theory and Application of Circuits and Electronics
______

Undergrad (Fall, Spring)
Prereq: None. Coreq: 6.002
Units: 1-1-1
Lecture: F3 (4-231) Recitation: TBA
______
Building on the framework of 6.002, provides a deeper understanding of the theory and applications of circuits and electronics.
A. Agarwal, J. del Alamo, J. H. Lang, D. J. Perreault
No textbook information available

6.170 Software Studio
______

Undergrad (Fall)
Prereq: 6.006; 6.005 or 6.031
Units: 4-0-8
URL: http://www.mit.edu/~6.170/
Lecture: MW2.30-4 (32-123) Recitation: R1 (38-166) or R2 (38-166) or R3 (38-166) or R11 (66-144) or R12 (66-144) or R1 (66-144) or R2 (66-144) or R3 (66-144) or R10 (38-166) or R11 (38-166) or R12 (38-166) or R4 (38-166)
______
Covers design and implementation of software systems, using web applications as the platform. Emphasizes the role of conceptual design in achieving clarity, simplicity, and modularity. Students complete open-ended individual assignments and a major team project. Enrollment may be limited.
D. N. Jackson
No textbook information available

6.172 Performance Engineering of Software Systems
______

Undergrad (Fall)
(Subject meets with 6.871)
Prereq: 6.004, 6.006; 6.005 or 6.031
Units: 3-12-3
Lecture: TR2.30-4 (34-101) Lab: F10-12 (4-265) or F1-3 (4-265) or F3-5 (4-265) or F10-12 (24-307) or F1-3 (34-301) or F3-5 (34-301) or F2-4 (34-304) or F3-5 (36-155)
______
Project-based introduction to building efficient, high-performance and scalable software systems. Topics include performance analysis, algorithmic techniques for high performance, instruction-level optimizations, vectorization, cache and memory hierarchy optimization, and parallel programming. Students taking graduate version complete additional assignments.
S. Amarasinghe, C. E. Leiserson
No textbook information available

6.175 Constructive Computer Architecture
______

Undergrad (Fall)
Prereq: 6.004
Units: 3-8-1
Lecture: MWF3 (34-302)
______
Illustrates a constructive (as opposed to a descriptive) approach to computer architecture. Topics include combinational and pipelined arithmetic-logic units (ALU), in-order pipelined microarchitectures, branch prediction, blocking and unblocking caches, interrupts, virtual memory support, cache coherence and multicore architectures. Labs in a modern Hardware Design Language (HDL) illustrate various aspects of microprocessor design, culminating in a term project in which students present a multicore design running on an FPGA board.
Arvind
No textbook information available

6.176 Pokerbots Competition
______

Undergrad (IAP) Can be repeated for credit
Prereq: None
Units: 1-0-5 [P/D/F]
______
Build autonomous poker players and aquire the knowledge of the game of poker. Showcase decision making skills, apply concepts in mathematics, computer science and economics. Provides instruction in programming, game theory, probability and statistics and machine learning. Concludes with a final competition and prizes. Enrollment limited
Staff

6.177 Building Programming Experience in Python
______

Not offered academic year 2016-2017Undergrad (IAP)
Prereq: None
Units: 1-0-5 [P/D/F]
______
Preparation for 6.01 aimed to sharpen skills in program design, implementation, and debugging in Python. Programming intensive, with one short structured assignment and a supervised, but highly individual, mandatory project presentation. Intended for students with some elementary programming experience (equivalent to AP Computer Science). Enrollment limited.
Staff

6.178 Introduction to Software Engineering in Java
______

Undergrad (IAP)
Prereq: None
Units: 1-1-4 [P/D/F]
______
Covers the fundamentals of Java, helping students develop intuition about object-oriented programming. Focuses on developing working software that solves real problems. Designed for students with little or no programming experience. Concepts covered useful to 6.005. Enrollment limited.
Staff

6.179 Introduction to C and C++
______

Undergrad (IAP)
Prereq: None
Units: 3-3-0 [P/D/F]
______
Fast-paced introduction to the C and C++ programming languages. Intended for those with experience in other languages who have never used C or C++. Students complete daily assignments, a small-scale individual project, and a mandatory online diagnostic test. Enrollment limited.
Staff

6.182 Psychoacoustics Project Laboratory
______

Undergrad (Spring) Institute Lab
Prereq: None
Units: 3-6-3
______
Introduces the methods used to measure human auditory abilities. Discusses auditory function, principles of psychoacoustic measurement, models for psychoacoustic performance, and experimental techniques. Project topics: absolute and differential auditory sensitivity, operating characteristics of human observers, span of auditory judgment, adaptive measurement procedures, and scaling sensory magnitudes. Knowledge of probability helpful. Students engage in extensive written and oral communication exercises.
L. D. Braida

6.S183-6.S192 Special Laboratory Subject in Electrical Engineering and Computer Science
______

Undergrad (IAP, Spring) Can be repeated for credit
Not offered regularly; consult department
Prereq: Permission of instructor
Units arranged [P/D/F]
______
Laboratory subject that covers content not offered in the regular curriculum. Consult department to learn of offerings for a particular term.
Consult Department

6.S193-6.S198 Special Laboratory Subject in Electrical Engineering and Computer Science
______

Undergrad (IAP, Spring) Can be repeated for credit
Prereq: Permission of instructor
Units arranged
6.S194: URL: http://www.eecs.mit.edu/academics-admissions/academic-information/subject-updates-st-2016
______
Laboratory subject that covers content not offered in the regular curriculum. Consult department to learn of offerings for a particular term.
Consult Department

Senior Projects

6.UAP Undergraduate Advanced Project
______

Undergrad (Fall, IAP, Spring, Summer) Can be repeated for credit
Prereq: 6.UAT
Units: 0-6-0
URL: http://www.eecs.mit.edu/ug/uap.html
Consult department TBA.
______
Research project for those students completing the SB degree, to be arranged by the student and an appropriate MIT faculty member. Students who register for this subject must consult the department undergraduate office. Students engage in extensive written communications exercises.
Consult Department Undergraduate Office
No textbook information available (Summer 2016); No required or recommended textbooks (Fall 2016)

6.UAR Seminar in Undergraduate Advanced Research
______

Undergrad (Fall, Spring) Can be repeated for credit
Prereq: 6.UR
Units: 2-0-4
URL: https://superurop.eecs.mit.edu/
Lecture: R4 (32-123)
______
Instruction in effective undergraduate research, including choosing and developing a research topic, surveying previous work and publications, research topics in EECS, industry best practices, design for robustness, technical presentation, authorship and collaboration, and ethics. Material covered over both fall and spring terms. Students engage in extensive written and oral communication exercises, in the context of an approved advanced research project. May be repeated for credit for a maximum of 12 units.
A. P. Chandrakasan, D. M. Freeman
No required or recommended textbooks

6.UAT Oral Communication
______

Undergrad (Fall, Spring)
Prereq: None
Units: 3-0-6
URL: https://courses.csail.mit.edu/6.UAT/main.php
Lecture: MW1 (34-101)
______
Provides instruction in aspects of effective technical oral presentations and exposure to communication skills useful in a workplace setting. Students create, give and revise a number of presentations of varying length targeting a range of different audiences.
T. L. Eng
No textbook information available

6.URS Undergraduate Research in Electrical Engineering and Computer Science
______

Undergrad (Fall, IAP, Spring, Summer) Can be repeated for credit
Prereq: Permission of instructor
Units arranged [P/D/F]
Consult department TBA.
______
Year-long individual research project arranged with appropriate faculty member or approved supervisor. Forms and instructions for the proposal and final report are available in the EECS Undergraduate Office.
A. P. Chandrakasan, D. M. Freeman
Textbooks arranged individually (Summer 2016); No required or recommended textbooks (Fall 2016)

Advanced Undergraduate Subjects and Graduate Subjects by Area

Systems Science and Control Engineering

6.207[J] Networks
______

Not offered academic year 2016-2017Undergrad (Spring) HASS Social Sciences
(Same subject as 14.15[J])
Prereq: 6.041B or 14.30
Units: 4-0-8
______
Highlights common principles that permeate the functioning of diverse technological, economic and social networks. Utilizes three sets of tools for analyzing networks--random graph models, optimization, and game theory--to study informational and learning cascades; economic and financial networks; social influence networks; formation of social groups; communication networks and the Internet; consensus and gossiping; spread and control of epidemics; control and use of energy networks; and biological networks.
Consult Department Headquarters

6.231 Dynamic Programming and Stochastic Control
______

Graduate (Spring)
Prereq: 6.041B or 18.204; 18.100A, 18.100B, or 18.100Q
Units: 3-0-9
URL: http://web.mit.edu/6.231/www/6231.html
______
Sequential decision-making via dynamic programming. Unified approach to optimal control of stochastic dynamic systems and Markovian decision problems. Applications in linear-quadratic control, inventory control, resource allocation, scheduling, and planning. Optimal decision making under perfect and imperfect state information. Certainty equivalent, open loop-feedback control, rollout, model predictive control, aggregation, and other suboptimal control methods. Infinite horizon problems: discounted, stochastic shortest path, average cost, and semi-Markov models. Value and policy iteration. Abstract models in dynamic programming. Approximate/neurodynamic programming. Simulation based methods. Discussion of current research on the solution of large-scale problems.
J. N. Tsitsiklis

6.241[J] Dynamic Systems and Control
______

Graduate (Spring)
(Same subject as 16.338[J])
Prereq: 6.003, 18.06
Units: 4-0-8
______
Linear, discrete- and continuous-time, multi-input-output systems in control, related areas. Least squares and matrix perturbation problems. State-space models, modes, stability, controllability, observability, transfer function matrices, poles and zeros, and minimality. Internal stability of interconnected systems, feedback compensators, state feedback, optimal regulation, observers, and observer-based compensators. Measures of control performance, robustness issues using singular values of transfer functions. Introductory ideas on nonlinear systems. Recommended prerequisite: 6.302.
M. A. Dahleh, A. Megretski, E. Frazzoli

6.245 Multivariable Control Systems
______

Not offered academic year 2016-2017Graduate (Fall)
Prereq: 6.241 or 16.31
Units: 3-0-9
URL: http://web.mit.edu/6.245/www/index.html
______
Computer-aided design methodologies for synthesis of multivariable feedback control systems. Performance and robustness trade-offs. Model-based compensators; Q-parameterization; ill-posed optimization problems; dynamic augmentation; linear-quadratic optimization of controllers; H-infinity controller design; Mu-synthesis; model and compensator simplification; nonlinear effects. Computer-aided (MATLAB) design homework using models of physical processes.
A. Megretski

6.246, 6.247 Advanced Topics in Control
______

Graduate (Spring) Can be repeated for credit
Not offered regularly; consult department
Prereq: Permission of instructor
Units: 3-0-9
______
Advanced study of topics in control. Specific focus varies from year to year.
Consult Department

6.248, 6.249 Advanced Topics in Numerical Methods
______

Graduate (Fall, Spring) Can be repeated for credit
Not offered regularly; consult department
Prereq: Permission of instructor
Units: 3-0-9
______
Advanced study of topics in numerical methods. Specific focus varies from year to year.
Consult Department

6.251[J] Introduction to Mathematical Programming
______

Graduate (Fall)
(Same subject as 15.081[J])
Prereq: 18.06
Units: 4-0-8
Lecture: TR1-2.30 (32-155) Recitation: F10 (36-156) or F12 (32-144)
______
Introduction to linear optimization and its extensions emphasizing both methodology and the underlying mathematical structures and geometrical ideas. Covers classical theory of linear programming as well as some recent advances in the field. Topics: simplex method; duality theory; sensitivity analysis; network flow problems; decomposition; integer programming; interior point algorithms for linear programming; and introduction to combinatorial optimization and NP-completeness.
J. N. Tsitsiklis, D. Bertsimas
Textbooks (Fall 2016)

6.252[J] Nonlinear Optimization
______

Graduate (Spring)
(Same subject as 15.084[J])
Prereq: 18.06; 18.100A, 18.100B, or 18.100C
Units: 4-0-8
______
Unified analytical and computational approach to nonlinear optimization problems. Unconstrained optimization methods include gradient, conjugate direction, Newton, sub-gradient and first-order methods. Constrained optimization methods include feasible directions, projection, interior point methods, and Lagrange multiplier methods. Convex analysis, Lagrangian relaxation, nondifferentiable optimization, and applications in integer programming. Comprehensive treatment of optimality conditions and Lagrange multipliers. Geometric approach to duality theory. Applications drawn from control, communications, power systems, and resource allocation problems.
R. M. Freund, D. P. Bertsekas, G. Perakis

6.253 Convex Analysis and Optimization
______

Not offered academic year 2016-2017Graduate (Spring)
Prereq: 18.06; 18.100A, 18.100B, or 18.100C
Units: 3-0-9
______
Core analytical issues of continuous optimization, duality, and saddle point theory, and development using a handful of unifying principles that can be easily visualized and readily understood. Discusses in detail the mathematical theory of convex sets and functions which are the basis for an intuitive, highly visual, geometrical approach to the subject. Convex optimization algorithms focus on large-scale problems, drawn from several types of applications, such as resource allocation and machine learning. Includes batch and incremental subgradient, cutting plane, proximal, and bundle methods.
D. P. Bertsekas

6.254 Game Theory with Engineering Applications
______

Not offered academic year 2016-2017Graduate (Fall)
Prereq: 6.041B
Units: 4-0-8
______
Introduction to fundamentals of game theory and mechanism design with motivations for each topic drawn from engineering applications (including distributed control of wireline/wireless communication networks, transportation networks, pricing). Emphasis on the foundations of the theory, mathematical tools, as well as modeling and the equilibrium notion in different environments. Topics include normal form games, supermodular games, dynamic games, repeated games, games with incomplete/imperfect information, mechanism design, cooperative game theory, and network games.
A. Ozdaglar

6.255[J] Optimization Methods
______

Graduate (Fall)
(Same subject as 15.093[J], IDS.200[J])
Prereq: 18.06
Units: 4-0-8
Lecture: TR2.30-4 (32-123) Recitation: W3 (66-168) or F1 (66-144) +final
______
Introduces the principal algorithms for linear, network, discrete, robust, nonlinear, dynamic optimization and optimal control. Emphasizes methodology and the underlying mathematical structures. Topics include the simplex method, network flow methods, branch and bound and cutting plane methods for discrete optimization, optimality conditions for nonlinear optimization, interior point methods for convex optimization, Newton's method, heuristic methods, and dynamic programming and optimal control methods.
D. Bertsimas, P. Parrilo
Textbooks (Fall 2016)

6.256 Algebraic Techniques and Semidefinite Optimization
______

Not offered academic year 2016-2017Graduate (Spring)
Prereq: 6.251 or 6.255
Units: 3-0-9
______
Theory and computational techniques for optimization problems involving polynomial equations and inequalities with particular, emphasis on the connections with semidefinite optimization. Develops algebraic and numerical approaches of general applicability, with a view towards methods that simultaneously incorporate both elements, stressing convexity-based ideas, complexity results, and efficient implementations. Examples from several engineering areas, in particular systems and control applications. Topics include semidefinite programming, resultants/discriminants, hyperbolic polynomials, Groebner bases, quantifier elimination, and sum of squares.
P. Parrilo

6.260, 6.261 Advanced Topics in Communications
______

Graduate (Fall, Spring) Can be repeated for credit
Not offered regularly; consult department
Prereq: Permission of instructor
Units: 3-0-9
______
Advanced study of topics in communications. Specific focus varies from year to year.
Consult Department

6.262 Discrete Stochastic Processes
______

Graduate (Spring)
Prereq: 6.041B, 6.431B or 18.204
Units: 4-0-8
______
Review of probability and laws of large numbers; Poisson counting process and renewal processes; Markov chains (including Markov decision theory), branching processes, birth-death processes, and semi-Markov processes; continuous-time Markov chains and reversibility; random walks, martingales, and large deviations; applications from queueing, communication, control, and operations research.
R. G. Gallager, V. W. S. Chan

6.263[J] Data-Communication Networks
______

Not offered academic year 2016-2017Graduate (Fall)
(Same subject as 16.37[J])
Prereq: 6.041B or 18.204
Units: 3-0-9
______
Provides an introduction to data networks with an analytic perspective, using telephone networks, wireless networks, optical networks, the Internet and data centers as primary applications. Presents basic tools for modeling and performance analysis accompanied by elementary, meaningful simulations. Develops insights for large networks by means of simple approximations. Draws upon concepts from queueing theory and optimization.
E. Modiano, D. Shah

6.265[J] Advanced Stochastic Processes
______

Graduate (Spring)
(Same subject as 15.070[J])
Prereq: 6.431B, 15.085J, 18.100A, 18.100B, or 18.100Q
Units: 3-0-9
______
Analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems; elements of large deviations theory; Brownian motion and reflected Brownian motion; stochastic integration and Ito calculus; functional limit theorems. Applications to finance theory, insurance, queueing and inventory models.
D. Gamarnik, G. Bresler

6.267 Heterogeneous Networks: Architecture, Transport, Proctocols, and Management
______

Not offered academic year 2016-2017Graduate (Fall)
Prereq: 6.041B or 6.042
Units: 4-0-8
______
Introduction to modern heterogeneous networks and the provision of heterogeneous services. Architectural principles, analysis, algorithmic techniques, performance analysis, and existing designs are developed and applied to understand current problems in network design and architecture. Begins with basic principles of networking. Emphasizes development of mathematical and algorithmic tools; applies them to understanding network layer design from the performance and scalability viewpoint. Concludes with network management and control, including the architecture and performance analysis of interconnected heterogeneous networks. Provides background and insight to understand current network literature and to perform research on networks with the aid of network design projects.
V. W. S. Chan, R. G. Gallager

6.268 Network Science and Models
______

Not offered academic year 2017-2018Graduate (Spring)
Prereq: 6.041B, 18.06
Units: 3-0-9
______
Introduces the main mathematical models used to describe large networks and dynamical processes that evolve on networks. Static models of random graphs, preferential attachment, and other graph evolution models. Epidemic propagation, opinion dynamics, social learning, and inference in networks. Applications drawn from social, economic, natural, and infrastructure networks, as well as networked decision systems such as sensor networks.
J. N. Tsitsiklis, P. Jaillet


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Produced: 14-OCT-2016 05:10 PM