Electrical Engineering And Computer Science (Course 6)

ELECTRICAL ENGINEERING AND COMPUTER SCIENCE (COURSE 6)ELECTRICAL ENGINEERING AND COMPUTERSCIENCE (COURSE 6)Basic Undergraduate Subjects6.0001 Introduction to Computer Science Programming inPythonPrereq: NoneU (Fall, Spring; rst half of term)3-0-3 unitsIntroduction to computer science and programming for studentswith little or no programming experience. Students develop skillsto program and use computational techniques to solve problems.Topics include the notion of computation, Python, simple algorithmsand data structures, testing and debugging, and algorithmiccomplexity. Combination of 6.0001 and 6.0002 counts as RESTsubject. Final given in the seventh week of the term.A. Bell, J. V. Guttag6.0002 Introduction to Computational Thinking and Data SciencePrereq: 6.0001 or permission of instructorU (Fall, Spring; second half of term)3-0-3 unitsProvides an introduction to using computation to understand realworld phenomena. Topics include plotting, stochastic programs,probability and statistics, random walks, Monte Carlo simulations,modeling data, optimization problems, and clustering. Combinationof 6.0001 and 6.0002 counts as REST subject.A. Bell, J. V. Guttag6.S00 Special Subject in Electrical Engineering and ComputerScience (New)Prereq: NoneU (Fall, Spring)Units arrangedCovers subject matter not o ered in the regular curriculum. Consultdepartment to learn of o erings for a particular term.A. Bell, W. E. L. Grimson, J. V. Guttag6.002 Circuits and ElectronicsPrereq: Physics II (GIR); Coreq: 2.087 or 18.03U (Fall, Spring)3-2-7 units. RESTFundamentals of linear systems and abstraction modeling throughlumped electronic circuits. Linear networks involving independentand dependent sources, resistors, capacitors and inductors.Extensions to include nonlinear resistors, switches, transistors,operational ampli ers and transducers. Dynamics of rst- andsecond-order networks; design in the time and frequency domains;signal and energy processing applications. Design exercises. Weeklylaboratory with microcontroller and transducers.J. H. Lang, T. Palacios, D. J. Perreault, J. Voldman6.003 Signal ProcessingPrereq: Calculus I (GIR) and 6.0001U (Fall, Spring)6-0-6 units. RESTFundamentals of signal processing, focusing on the use of Fouriermethods to analyze and process signals such as sounds and images.Topics include Fourier series, Fourier transforms, the Discrete FourierTransform, sampling, convolution, deconvolution, ltering, noisereduction, and compression. Applications draw broadly from areas ofcontemporary interest with emphasis on both analysis and design.D. M. Freeman, A. Hartz6.004 Computation StructuresPrereq: Physics II (GIR) and 6.0001U (Fall, Spring)4-0-8 units. RESTProvides an introduction to the design of digital systems andcomputer architecture. Emphasizes expressing all hardware designsin a high-level hardware language and synthesizing the designs.Topics include combinational and sequential circuits, instruction setabstraction for programmable hardware, single-cycle and pipelinedprocessor implementations, multi-level memory hierarchies, virtualmemory, exceptions and I/O, and parallel systems.Arvind, S. Z. Hanono Wachman, D. SanchezElectrical Engineering and Computer Science (Course 6) 3

ELECTRICAL ENGINEERING AND COMPUTER SCIENCE (COURSE 6)6.006 Introduction to AlgorithmsPrereq: 6.042[J] and (6.0001 or Coreq: 6.009)U (Fall, Spring)4-0-8 unitsIntroduction to mathematical modeling of computational problems,as well as common algorithms, algorithmic paradigms, anddata structures used to solve these problems. Emphasizes therelationship between algorithms and programming, and introducesbasic performance measures and analysis techniques for theseproblems. Enrollment may be limited.E. Demaine, S. Devadas6.008 Introduction to InferencePrereq: Calculus II (GIR) or permission of instructorU (Fall)4-4-4 units. Institute LABIntroduces probabilistic modeling for problems of inferenceand machine learning from data, emphasizing analyticaland computational aspects. Distributions, marginalization,conditioning, and structure, including graphical and neuralnetwork representations. Belief propagation, decision-making,classi cation, estimation, and prediction. Sampling methods andanalysis. Introduces asymptotic analysis and information measures.Computational laboratory component explores the conceptsintroduced in class in the context of contemporary applications.Students design inference algorithms, investigate their behavior onreal data, and discuss experimental results.P. Golland, G. W. Wornell6.009 Fundamentals of ProgrammingPrereq: 6.0001U (Fall, Spring)2-4-6 units. Institute LABIntroduces fundamental concepts of programming. Designedto develop skills in applying basic methods from programminglanguages to abstract problems. Topics include programming andPython basics, computational concepts, so ware engineering,algorithmic techniques, data types, and recursion. Lab componentconsists of so ware design, construction, and implementation ofdesign. Enrollment may be limited.D. S. Boning, A. Chlipala, S. Devadas, A. Hartz4 Electrical Engineering and Computer Science (Course 6)6.01 Introduction to EECS via RoboticsPrereq: 6.0001 or permission of instructorAcad Year 2020-2021: Not o eredAcad Year 2021-2022: U (Spring)2-4-6 units. Institute LABAn integrated introduction to electrical engineering and computerscience, taught using substantial laboratory experiments withmobile robots. Key issues in the design of engineered artifactsoperating in the natural world: measuring and modeling systembehaviors; assessing errors in sensors and e ectors; specifyingtasks; designing solutions based on analytical and computationalmodels; planning, executing, and evaluating experimental testsof performance; re ning models and designs. Issues addressed inthe context of computer programs, control systems, probabilisticinference problems, circuits and transducers, which all playimportant roles in achieving robust operation of a large variety ofengineered systems.D. M. Freeman, A. Hartz, L. P. Kaelbling, T. Lozano-Perez6.011 Signals, Systems and InferencePrereq: 6.003 and (6.008, 6.041, or 18.600)U (Spring)4-0-8 unitsCovers signals, systems and inference in communication, controland signal processing. Topics include input-output and statespace models of linear systems driven by deterministic and randomsignals; time- and transform-domain representations in discrete andcontinuous time; and group delay. State feedback and observers.Probabilistic models; stochastic processes, correlation functions,power spectra, spectral factorization. Least-mean square errorestimation; Wiener ltering. Hypothesis testing; detection; matched lters.A. V. Oppenheim, G. C. Verghese

ELECTRICAL ENGINEERING AND COMPUTER SCIENCE (COURSE 6)6.012 Nanoelectronics and Computing SystemsPrereq: 6.002U (Fall, Spring)4-0-8 unitsStudies interaction between materials, semiconductor physics,electronic devices, and computing systems. Develops intuitionof how transistors operate. Topics range from introductorysemiconductor physics to modern state-of-the-art nano-scaledevices. Considers how innovations in devices have driven historicalprogress in computing, and explores ideas for further improvementsin devices and computing. Students apply material to understandhow building improved computing systems requires knowledge ofdevices, and how making the correct device requires knowledgeof computing systems. Includes a design project for practicalapplication of concepts, and labs for experience building silicontransistors and devices.A. I. Akinwande, J. Kong, T. Palacios, M. Shulaker6.013 Electromagnetics Waves and ApplicationsPrereq: Calculus II (GIR) and Physics II (GIR)U (Spring)3-5-4 unitsAnalysis and design of modern applications that employelectromagnetic phenomena for signals and power transmissionin RF, microwaves, optical and wireless communication systems.Fundamentals include dynamic solutions for Maxwell's equations;electromagnetic power and energy, waves in media, metallic anddielectric waveguides, radiation, and di raction; resonance; lters;and acoustic analogs. Lab activities range from building to testingof devices and systems (e.g., antenna arrays, radars, dielectricwaveguides). Students work in teams on self-proposed makerstyle design projects with a focus on fostering creativity, teamwork,and debugging skills. 6.002 and 6.003 are recommended but notrequired.K. O'Brien, L. Daniel6.014 Electromagnetic Fields, Forces and MotionSubject meets with 6.640Prereq: Physics II (GIR) and 18.03U (Fall)4-0-8 unitsStudy of electromagnetics and electromagnetic energy conversionleading to an understanding of devices, including electromagneticsensors, actuators, motors and generators. Quasistatic Maxwell'sequations and the Lorentz force law. Studies of the quasistatic eldsand their sources through solutions of Poisson's and Laplace'sequations. Boundary conditions and multi-region boundary-valueproblems. Steady-state conduction, polarization, and magnetization.Charge conservation and relaxation, and magnetic induction anddi usion. Extension to moving materials. Electric and magneticforces and force densities derived from energy, and stress tensors.Extensive use of engineering examples. Students taking graduateversion complete additional assignments.J. L. Kirtley, Jr., J. H. Lang6.02 Introduction to EECS via Communication NetworksPrereq: 6.0001U (Fall)4-4-4 units. Institute LABStudies key concepts, systems, and algorithms to reliablycommunicate data in settings ranging from the cellular phonenetwork and the Internet to deep space. Weekly laboratoryexperiments explore these areas in depth. Topics presented in threemodules - bits, signals, and packets - spanning the multiple layersof a communication system. Bits module includes information,entropy, data compression algorithms, and error correction withblock and convolutional codes. Signals module includes modelingphysical channels and noise, signal design, ltering and detection,modulation, and frequency-division multiplexing. Packets moduleincludes switching and queuing principles, media access control,routing protocols, and data transport protocols.K. LaCurtsElectrical Engineering and Computer Science (Course 6) 5