Between 6.001 and 6.170: A Gentle Introduction to Software Engineering in Java
Justin Mazzola Paluska, Vikash Mansinghka
Mon-Fri, Jan 10-13, 18-21, 11am-01:00pm, 37-312
Enrollment limited: first come, first served
Signup by: 03-Jan-2005
Limited to 30 participants.
Participants requested to attend all sessions (non-series)
Prereq: 6.001; NO other programming experience
Presumes only Scheme. Presents Java and software engineering fundamentals through guided programming exercises and brief, painless lectures. Topics include your first words of Java, conceptual links between Java and Scheme, the tools Java provides (and appropriate Java idioms) for organizing sofware systems, and basic debugging and debuggers. Also, build a register-machine-level computer simulator and a basic zephyr-style chat system. Sponsored by Tau Beta Pi and the EECS Department.
Web: http://web.mit.edu/tbp/www/tbp-teach
Contact: Justin Mazzola Paluska, tbp-software-engineering@mit.edu
Cosponsor: Electrical Engineering and Computer Science
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Linear Algebra Demystified
Jonathan Pottharst (Harvard Doctoral Math Student), Vikash Mansinghka
Mon-Thu, Jan 10-13, 18-20, 24-27, 04-06:00pm, 34-301
Enrollment limited: first come, first served
Limited to 30 participants.
Participants requested to attend all sessions (non-series)
Prereq: Desire to master linear algebra; some classroom exposure
This non-credit class explores conceptual tools required to understand linear algebra and apply it to engineering problems. It will focus on conceptual precision and visual intuition, aiming to make the meaning of matrices intuitive. Topics include linear maps as matrices, invertibility, eigen-stuff, geometry, least squares approximations, and linear systems analysis.
Problem sessions 4-5pm, lectures 5-6pm.
Class is centered around problem-solving tutorials, short readings and mini-lectures, with instructors circulating to answer your questions. Intended for students who have seen linear algebra through 18.06 or various engineering classes, and have discovered they need to understand it better.
Sponsored by Tau Beta Pi and the EECS Department.
Web: http://web.mit.edu/tbp/www/tbp-teach
Contact: Jonathan Pottharst, tbp-linear-algebra@mit.edu
Cosponsor: Electrical Engineering and Computer Science
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