In this course we begin by stating many wonderful theorems in analysis and proceed to prove them one by one. In contrast to usual courses (where we learn techniques and see results as "applications of those techniques). We take a somewhat experimental approach in stating the results and then exploring the techniques to prove them. The theorems themselves have the common feature that the statements are easy to understand but the proofs are non-trivial and instructive. And the techniques involve analysis.

We intend to cover a subset of the following theoremes: Isoperimetric inequality, infinitude of primes in arithmetic progressions, Weyl's equidistribution theorem on the circle, Shannon's source coding theorem, undertainty, principles including Heisenberg's Wigner's law for eigenvalue of a random matrix, Picard's theorem on the range of an entire function, principal component analysis to reduce dimensionality of data.....

Prerequisites : Real analysis, complex analysis, basic probability, linear algebra, groups. It would help to know or to concurrently take a course in measure theory and /or functional analysis.


Recommended books