Syllabus
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Course Code: MT-CSE-20-11 Course Name: Mathematical Foundations of Computer Science |
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| MODULE NO / UNIT | COURSE SYLLABUS CONTENTS OF MODULE | NOTES |
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| 1 | Probability mass, density, and cumulative distribution functions, parametric families of distributions, Expected value, variance, conditional expectation, Applications of the univariate and multivariate, Central Limit Theorem, Probabilistic inequalities, Markov chains. |
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| 2 | Random samples, sampling distributions of estimators, Methods of Moments and Maximum Likelihood, Recent Trends in various distribution functions in mathematical field of computer science for varying fields. | |
| 3 | Statistical inference, Introduction to multivariate statistical models: regression and classification problems, principal components analysis, the problem of over fitting model assessment. | |
| 4 | Graph Theory: Isomorphism, Planar graphs, graph colouring, Hamilton circuits and Euler cycles. Permutations and Combinations with and without repetition, Specialized techniques to solve combinatorial enumeration problems. |
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