1 
Lecture
1: Introduction to modular arithmetic. An application to the ISBN book number was explained. For another introduction to modular arithmetic take a look at this Youtube clip. Then take a look at this clip, this clip and this clip 
2 
Lecture
2: Explained Euclid's algorithm for finding the greatest common divisor of two numbers, and used it to find the inverse of some number n modulo m. An application of modular arithmetic to IBAN bank numbers was explained. Take a look at this clip for another example of using the Euclidean algorithm to find the inverse of a number in modular arithmetic. For more background on modular arithmetic take a look at the wikipedia page here. 
3 
Lecture
3: Explained the basic ideas underlying cryptography. Discussed the Enigma machine and an affine cryptosystem on single letter message units. For more background on the Enigma machine take a look at the wikipedia page here. For more background on affine cryptosystems take a look at the wikipedia page here. 
4

Lecture
4: Deciphered an enciphered message sent from Agent 007. 
5

Lecture
5: Explained the Chinese Remainder Theorem. For more background on the Chinese Remainder Theorem take a look at the wikipedia page here. Also, take a look at this youtube explanation which uses easily calculated numbers, 
6

Lecture
6: Introduced Euler's phi (or totient) function. For more background on Euler's phi function take a look at the wikipedia page here. 
7

Lecture
7: Began with the quote "both Gauss and less mathematicians may be justified in rejoicing that there is one science at any rate [number theory], and that their own, whose very remoteness from ordinary human activities should keep it gentle and clean." from G.H. Hardy's A Mathematicians Apology. This short book is well worth a read and is available online here. Then explained the RSA public key cryptosystem. For more background on the RSA cryptosystem take a look at the wikipedia page here. 
8

Lecture
8: Stated and illustrated Euler's Theorem. Then stated and proved a special case known as Fermat's little theorem. For more background on Euler's Theorem take a look at the wikipedia page here. For more background on Fermat's little heorem take a look at the wikipedia page here. 
9

Lecture
9: Introduced the notion of a matrix and the operations of addition, subtraction and multiplication. For more background on matrix addition look at the wikipedia page here. For more background on matrix multiplication look at the wikipedia page here. Take a look at this clip for examples of matrix multiplication. 
10

Lecture 10 : Explained the notion of an affine matrix cryptosystem. 
11

Lecture
11: Deciphered a ciphertext obtained from an affine matrix cryptosystem. In the process I got lots of practice of matrix multiplication. 
12

Lecture
12: Introduced the concept of a linear transformation of the plane. Showed that reflection in a line through the origin is a linear transormation. For more background on linear transformations take a look at the Open Corseware notes from MIT here. 
13

Lecture
13: Explained why every linear transformation of the plane can be represented by a 2x2 matrix. Stated a theorem that asserts that composition of transformations corresponds to multiplication of matrices. Matrix multiplication has been invented just so that this theorem is true. I didn't get around to deriving the matrix representing rotation through an angle theta about the origin. See the slides of a previous year's lecture for this important derivation. 
14

Lecture
14: Illustrated the GaussJordan method for inverting a matrix. The method uses a sequence of row operations. 
15

Lecture
15: Explained why the GaussJordan method for finding the inverse of a matrix works. Gave an example to illustrate that row operations can be used to solve systems of linear equations arising from "real life" problems. For more background on systems of linear equations take a look at the wikipedia page here. 
16

Lecture
16: Defined the determinant and adjoint of a 2x2 matrix. Gave a formula for the inverse of a 2x2 matrix in terms of its determinant and adjoint. Explained that the determinant of a 2x2 matrix is equal to the area of a certain parallelogram up to sign. 
17

Lecture
17: Proved that the determinant of a 2x2 matrix is equal to the area of a certain parallelogram up to sign. Then introduced and illustrated the notions of eigenvector and eigenvalue of a matrix. 
18

Lecture
18: Explained how eigenvectors are involved in Google's page rank algorithm. (I intensionally over simplified the explanation. In particular, the importance I_{n} of a page is determined from the full network of pages on the internet and not just those [8 in my explanation] containg the given searched words.) More details on the page rank algorithm can be found here. Also stated and illustrated the important HamiltonCayley Theorem. 
19

Lecture
19: Explained how to find eigenvalues of a 2x2 matrix using the characteristic equation. Explained how to find eigenvectors for the given eigenvalues. Derived the recurrence relation F_{n} = F_{n1} + F_{n2} for the number of rabbits in a field after n months, based on some assumptions about rabbit breeding. 
20

Lecture
20: Talked about various occurences of the Golden Ratio. 
21

Lecture
21: Explained how to express a suitable 2x2 matrix A in the form A=T^{1} D T where D is diagonal. Here "suitable" means that A must have two eigenvectors such that the matrix T containing the two eigenvectors as columns is invertible. Used the above expression to find a formula for the terms F_{n} in the Fibonacci sequence. 
22

Lecture
22: Used eigenvalues and eigenvectors to study a diseased population of frogs. 
23

Lecture
23: Did some revision. 
24

Lecture
Sem
II: Did a bit more revision. 