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(Created page with "Welcome to the Matrix Analysis class wiki. Instructor: Christopher Hillar Scribe: Sarah Marzen Web co-ordinator: Mayur Mudigonda")
 
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Welcome to the Matrix Analysis class wiki.
This is the spring '13 Matrix analysis class wiki


Instructor: Christopher Hillar
== Course description ==
Scribe: Sarah Marzen
 
Web co-ordinator: Mayur Mudigonda
This is the first ever course of its kind on Matrix Analysis. Matrices are generally awesome and since most of us use Matlab, it would help to know more about them.
 
Also blah blah blah and blah!
 
=== Instructors ===
 
[Chris Hillar]
* Email:
* Office: 570 Evans
* Office hours: immediately following lecture or through e-mail
 
[Sarah Marzen], Scribe and GSI
* Email:
* Office: 567 Evans
 
[http://redwood.berkeley.edu/mayur Mayur Mudigonda]
 
=== Lectures ===
* '''Location''': 560 Evans (Redwood Center Conference Hall)
* '''Times''': First and Third Thursdays - 3:30 PM to 5 PM
 
 
=== Enrollment information ===
 
=== Email list and forum ===
 
=== Grading ===
 
=== Required background===
Prerequisites are calculus, ordinary differential equations, basic probability and statistics, and linear algebra. Familiarity with programming in a high level language such as Matlab is also required.
 
=== Textbooks ===

Revision as of 04:26, 15 February 2013

This is the spring '13 Matrix analysis class wiki

Course description

This is the first ever course of its kind on Matrix Analysis. Matrices are generally awesome and since most of us use Matlab, it would help to know more about them.

Also blah blah blah and blah!

Instructors

[Chris Hillar]

  • Email:
  • Office: 570 Evans
  • Office hours: immediately following lecture or through e-mail

[Sarah Marzen], Scribe and GSI

  • Email:
  • Office: 567 Evans

Mayur Mudigonda

Lectures

  • Location: 560 Evans (Redwood Center Conference Hall)
  • Times: First and Third Thursdays - 3:30 PM to 5 PM


Enrollment information

Email list and forum

Grading

Required background

Prerequisites are calculus, ordinary differential equations, basic probability and statistics, and linear algebra. Familiarity with programming in a high level language such as Matlab is also required.

Textbooks