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HU Credits:
4
Degree/Cycle:
1st degree (Bachelor)
Responsible Department:
Statistics
Semester:
1st Semester
Teaching Languages:
Hebrew
Campus:
Mt. Scopus
Course/Module Coordinator:
Moshe Haviv
Coordinator Office Hours:
לפי תאום מראש
Teaching Staff:
Prof Moshe Haviv
Ms. rachel buchuk
Course/Module description:
See below
Course/Module aims:
The main goal of the course is to introduce to the students basic tools in Linear Algebra.
Learning outcomes - On successful completion of this module, students should be able to:
1. To quote and apply the definitions that were presented in the course.
2. To solve independently exercises which related to the covered material.
3. To describe at least 1 example in the context of any claim which studeid in the class.
4. To prove independently simple variants of claims that were stated in class.
Attendance requirements(%):
No attendance requirement
Teaching arrangement and method of instruction:
The methodical material of the course will be presented weekly in the
form of class lectures.
The lectures will be accompany by practical lessons and weekly exercises. In addition there are avaliable videos in the web which cover part of the material.
Course/Module Content:
In this course we will study essential topics in Linear Algebra.
The topics that we wil learn are:
1. Vectors:
(a) summation, scalar multiplication, linear combinations
(b) dot product, norm, distance and angles between vectors, projection
one vector on another, orthogonal vectors
(c) linear dependence and independence, linear space, span of vectors,
basis and dimension of a linear space
(d) projecting a vector on a space, Gram-Shmidt process
2. Matrices
(a) the rows and columns spaces
(b) the rank of a matrix
(c) summation and multiplication of matrices
(d) linear transformation and matrices
(e) system of linear equations
(f) the QR factorization of a matrix
(g) right and left inverses.
(h) invertible matrices and the inverse matrix
(i) solving system of linear equations
(j) generalized inverses
(k) elementary row operations
(l) determinants
3. Least squares
(a) least square solution of linear systems
(b) the projection matrix
(c) linear regression
4. Eigenvalues and eigenvectors of symmetric matrices
Required Reading:
There is no required reading material.
Additional Reading Material:
1.Link to course videos: http://www.youtube.com/playlist?list&eq;PLbgUifVRG9N5UsI0U19ko-3LZmWHh9nbk
2. Introduction to Applied Linear Algebra Vectors, Matrices, and Least Squares by Stephen Boyd and Lieven Vandenberghe, 2017
3. Linear Algebra by Synour Lipschutz
Course/Module evaluation:
End of year written/oral examination 100 %
Presentation 0 %
Participation in Tutorials 0 %
Project work 0 %
Assignments 0 %
Reports 0 %
Research project 0 %
Quizzes 0 %
Other 0 %
Additional information:
Nine out of 13 weekly assignments are required to handed in. Three points will be deducted for any missing assignment.
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