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source: Technion 2015年11月23日
Algebra 1M - international
Course no. 104016
Dr. Aviv Censor
Technion - International school of engineering
01 - Introduction 9:13
02 - Sets of numbers 41:58
03 - Fields 32:01
04 - More properties of fields 18:53
05 - Complex numbers 47:34
06 - The Complex conjugate, the modulus and division 51:30
07 - Polar form 27:59
08 - Multiplication, division, powers and roots 39:26
09 - Polynomials 16:40
10 - Roots of polynomials 1:06:26
11 - Matrices 35:01
12 - Operations on matrices 21:49
13 - Matrix multiplication 21:48
14 - Properties of matrix multiplication 33:42
15 - Systems of linear equations 22:20
16 - Solving systems of linear equations 17:01
17 - The method of row-reduction 1:02:06
18 - Determining the number of solutions 47:38
19 - Homogeneous vs. non homogeneous systems 45:31
20 - The space R^n 29:12
21 - Vector spaces 46:18
22 - Vector subspaces 30:24
23 - More examples of subspaces 21:23
24 - Intersections and sums of subspaces 27:05
25 - Direct sums of subspaces 29:22
26 - Linear combinations and spans 35:20
27 - Determining if v belongs to a span 18:54
28 - Linear independence 20:14
29 - Determining linear independence 59:07
30 - Theorems about linear independence 39:56
31 - More on spans and linear independence 37:26
32 - Bases of vector spaces 20:18
33 - The dimension of a vector space 21:57
34 - Properties of bases 17:44
35 - Properties of bases (continued) 1:01:48
36 - Bases and dimensions of subspaces 52:16
37 - Coordinate vectors 34:15
38 - The dimension of Row(A) and Col(A) 44:47
39 - The rank-nullity theorem 32:41
40 - Invertible matrices 20:57
41 - Determining invertibility and finding the inverse 1:01:07
42 - Determinants 34:21
43 - Properties of determinants 31:33
44 - Invertibility and the determinant 21:08
45 - The matrix adj(A) 30:43
46 - Cramer's rule 13:12
47 - Which method is better? 7:02
48 - Linear maps 37:19
49 - Ker(T) and Im(T) 34:28
50 - Some geometric examples 26:48
51 - Properties of Ker(T) and Im(T) 40:07
52 - The rank of T 25:18
53 - The rank-nullity theorem revisited 37:12
54 - Matrix representation of linear maps 42:07
55 - Matrix representation of linear maps (continued) 1:00:27
56 - Operations on linear maps 58:21
57 - Compatability with operations on matrix representations 32:28
58 - Isomorphism 41:42
59 - Hom(V,W) 44:11
60 - Similarity of matrices 1:10:35
61 - Properties of similar matrices 22:29
62 - Diagonalization 25:32
63 - Diagonalization - a simple example 47:20
64 - Finding eigenvalues and eigenvectors 1:11:38
65 - An example 34:59
66 - Multiplicities of eigenvalues 33:11
67 - More on eigenvalues 1:13:41
68 - Powers of diagonalizable matrices 10:51
69 - The Cayley-Hamilton theorem 10:35
70 - Inner product 1:05:08
71 - Norm 30:24
72 - Inner product and norm give geometry 53:46
73 - Orthogonality 57:14
4 comments:
Fantastic!!! Thanks Dr. Aviv Censor!!
Really inspiring lectures
Algebra Can also Be Useful in Life Outside of the Workplace. I have found Algebra is helping in making financial decisions. I use Algebra every year to pick a health care plan for my family with the help of using two-variable equations to find the break-even point for each option. I have used Algebra in choosing cell phone plans. There are many direct and effective means of doing so, but it is a nice side-benefit that the two subject areas reinforce one another.
Very inspiring lecturer..
Made so many things much easier than before!
Loved every lecture!
Very inspiring Lecturer..
Made many thing much understood than before..
Loved and enjoyed the lectures very much!
Thank you!
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