Learnizo - Online Tuition Platform Logo
Chat with us on WhatsAppCall Learnizo

KTU 2024 Scheme · Semester 3 · Group A

Mathematics for Computer and Information Science 3 (GAMAT301) Syllabus

Official KTU 2024 Scheme syllabus for Mathematics for Computer and Information Science 3, Semester 3, Group A (Computer Science and Engineering).

This page compiles APJ Abdul Kalam Technological University's officially published 2024 Scheme syllabus for Computer Science and Engineering, Semester 3, sourced directly from KTU's official website (ktu.edu.in). Learnizo is an independent online tuition platform and is not affiliated with, endorsed by, or officially connected to APJKTU. The university may revise syllabus content after this page was last updated — always cross-check with the official KTU source for the current, authoritative version.

Course Code

GAMAT301

Credits

3

Teaching Hours

3:0:0:0 (L:T:P:R)

CIE Marks

40

ESE Marks

60

Exam Duration

2 Hrs 30 Min

Prerequisites

Basic calculus

Semester

Semester 3

Course Objective

To familiarize students with the foundations of probability and analysis of random processes used in various applications in engineering and science.

Module-wise Syllabus

Module 1

9 contact hours

Random variables, discrete random variables and their probability distributions, cumulative distribution function, expectation, mean and variance, the binomial probability distribution, the Poisson probability distribution, Poisson distribution as a limit of the binomial distribution, joint pmf of two discrete random variables, marginal pmf, independent random variables, expected value of a function of two discrete variables.

Module 2

9 contact hours

Continuous random variables and their probability distributions, cumulative distribution function, expectation, mean and variance, uniform, normal and exponential distributions, joint pdf of two continuous random variables, marginal pdf, independent random variables, expected value of a function of two continuous variables.

Module 3

9 contact hours

Limit theorems: Markov's inequality, Chebyshev's inequality, strong law of large numbers (without proof), central limit theorem (without proof). Stochastic processes: discrete-time process, continuous-time process, counting processes, the Poisson process, interarrival times (theorems without proof).

Module 4

9 contact hours

Markov chains, random walk model, Chapman-Kolmogorov equations, classification of states, irreducible Markov chain, recurrent state, transient state, long-run proportions (theorems without proof).

Course Outcomes

  • CO1Understand the concept, properties and important models of discrete random variables and apply them to suitable random phenomena.
  • CO2Understand the concept, properties and important models of continuous random variables and apply them to suitable random phenomena.
  • CO3Familiarize and apply limit theorems and understand the fundamental characteristics of stochastic processes.
  • CO4Solve problems involving Markov chains, understand their theoretical foundations, and apply them to model and predict the behaviour of various stochastic processes.

Assessment Pattern (CIE: 40 marks, ESE: 60 marks)

Continuous Internal Evaluation (CIE)

Attendance5
Assignment / Microproject15
Internal Examination 1 (Written)10
Internal Examination 2 (Written)10

End Semester Examination (ESE)

Total 60 marks, 2 Hrs 30 Min. See the official KTU syllabus document for the exact Part A / Part B question pattern for this course.

Textbooks & Reference Books

Textbooks

  • Probability and Statistics for Engineering and the Sciences — Devore J. L. (Cengage Learning, 9th edition, 2016)
  • Introduction to Probability Models — Sheldon M. Ross (Academic Press, 13th edition, 2024)

Reference Books

  • Probability and Random Processes for Electrical and Computer Engineers — John A. Gubner (Cambridge University Press, 2012)
  • Probability Models for Computer Science — Sheldon M. Ross (Academic Press, 1st edition, 2001)
  • Probability, Random Variables and Stochastic Processes — Papoulis, A. & Pillai, S.U. (Tata McGraw Hill, 4th edition, 2002)
  • Probability, Statistics and Random Processes — Kousalya Pappu (Pearson, 2013)

Frequently Asked Questions

How many credits is KTU Mathematics for Computer and Information Science 3 (GAMAT301)?

3 credits, with 3:0:0:0 (L:T:P:R) teaching hours per week, under the KTU 2024 Scheme.

How many modules are in the GAMAT301 syllabus?

4 modules, 36 total contact hours.

What is the CIE and ESE mark split for this course?

CIE (Continuous Internal Evaluation): 40 marks. ESE (End Semester Examination): 60 marks, 2 Hrs 30 Min. Total: 100 marks.

What are the recommended textbooks for GAMAT301?

Probability and Statistics for Engineering and the Sciences (Devore J. L.); Introduction to Probability Models (Sheldon M. Ross).

Is this syllabus specific to one branch, or common to others too?

This Semester 3 course is listed under Group A at KTU under the 2024 Scheme — check the course header above for which branches it's common to.

Need help with KTU Engineering Mathematics?

Learnizo offers live, 1-on-1 online tuition for KTU engineering mathematics — matched to your exact module and semester.

Explore KTU Maths Tuition