| Course Outline | General Information | Study Material | Lectures (classwise) | Problems, Exams and Assignments (updated) |
The course consists of 3 lecture hours (a lecture hour is of 50 minutes) per week.
The basic thrust of the course would be to study probability and stochastic processes and to learn their applications to computer science.
We will try to stick to the basic course outline as given in this page.
| Class Timings: | |
| The necessary evil - marks, exam, etc.: | End-sem: 50, Internal evaluation: 50 |
| Books |
(B1) A First Course in Probability Sheldon Ross Pearson. (B2) Probability and Computing: Randomized Algorithms and Probabilistic Analysis Michael Mitzenmacher and Eli Upfal Cambridge. (B3) An Introduction to Probability Theory and its Applications: Volume I William Feller John Wiley & Sons. (B4) Introduction to Probability Theory P. G. Hoel, S. C. Port and C. J. Stone University Book Stall/Houghton Mifflin, New Delhi/New York. (B5) The Art of Computer Programming: Seminumerical Algorithms, Vol. 2 Donald E. Knuth Pearson (B6) Invitation to Discrete Mathematics J. Matousek and J. Nesetril Clarendon Press, Oxford (B7) Applied Combinatorics Fred S. Roberts and B. Tesman Pearson, Prentice Hall (B8) Introduction to Probability Dimitri P. Bertsekas and John N. Tsitsiklis Athena Scientific, Massachusetts (B9) Algorithm Design J. Kleinberg and E. Tardos Pearson (B10) The Probabilistic Method Noga Alon and Joel H. Spencer Wiley (B11) Proofs from THE BOOK Martin Aigner and Gunter M. Ziegler Springer (B12) Counting: The Art of Enumerative Combinatorics George E. Martin Springer |
| Web Resources |
(W1) Richard Weber's course on Probability for first year mathematicians at Cambridge
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| LECTURE DATES | TOPICS | NOTES (pdf) | BOOKS |
| Class Tests | Date, Time and Venue | SOLUTIONS |
| ASSIGNMENTS | POSTED ON | SUBMISSION DEADLINE | SOLUTIONS |