About Mathematics for Information Science 3 (GAMAT301)
Mathematics for Computer and Information Science – 3 (GAMAT301) is a third-semester course in the KTU B.Tech 2024 scheme for Group A branches such as CSE, IT and AI & DS. It covers probability and random processes, the maths behind machine learning, data science, networking and the analysis of algorithms.
Syllabus
- Module 1: Discrete random variables: probability distributions, mean and variance, the Binomial and Poisson distributions, and joint distributions of two variables.
- Module 2: Continuous random variables: the Uniform, Normal and Exponential distributions, and joint probability density functions.
- Module 3: Limit theorems (Markov's and Chebyshev's inequalities, the law of large numbers, the central limit theorem), stochastic processes and the Poisson process.
- Module 4: Markov chains: the random walk model, Chapman–Kolmogorov equations, classification of states, and long-run proportions.
Exam pattern
The end-semester exam is for 60 marks: 8 short questions of 3 marks each, plus 4 questions of 9 marks each, one from each module. Internal assessment adds 40 marks.
Study tips
Practise numerical problems from every module, especially Binomial, Poisson and Normal distributions and Markov chain transition probabilities. Learn the standard formulas for mean and variance, and solve previous question papers to spot repeated problem types.
Notes and resources
Find module-wise notes, solved problems, previous year question papers and the syllabus for GAMAT301 here, shared by KTU students and teachers.