munotes®
Sign in
Home / Syllabus / B.E. (Artificial Intelligence and Data Science) / SY BE AI and DS / Semester 3 / Mathematics for Computer Engineering

B.E. (Artificial Intelligence and Data Science) Mathematics for Computer Engineering Syllabus - Mumbai University 2026

This is the SY BE AI and DS syllabus under NEP 2020, in force from the academic year 2025-26. The third and fourth years of this degree are still taught on the earlier CBCS REV-2019 'C' Scheme, because the University has published no NEP syllabus for Semesters V to VIII of any engineering branch.

Mathematics for Computer Engineering.pdf
Semester 3 · SY BE AI and DS · NEP 2020

Loading syllabus...

Syllabus for Mathematics for Computer Engineering

Semester 3 · SY BE AI and DS · NEP 2020

Module 0: Prerequisite

  • Complex Numbers, Probability, Central tendencies and dispersion in Statistical techniques, Baye's theorem, Random variable, Discrete and Continuous random variables.
  • 1. Characteristic Equation, Eigenvalues and
  • Eigenvectors, and properties (without proof)
  • 2. Cayley-Hamilton Theorem (without proof),

Module I: Linear Algebra (Theory of Matrices) 5 hours

  • verification and reduction of higher degree polynomials 3. Similarity of matrices, diagonalizable and non-diagonalizable matrices
  • Self-learning Topics: Derogatory and non-derogatory
  • matrices, Functions of Square Matrix, Linear
  • Transformations, Quadratic forms.

Module II: Linear and Non-Linear Programming Problems 5 hours

  • 1. Types of solutions, Standard and Canonical of LPP, Basic and Feasible solutions, slack variables, surplus variables, Simplex method. 2. NLPP with one and two equality constraint (two or three variables) using the method of Lagrange's multipliers Self-learning Topics: Sensitivity Analysis, Big-M method, Artificial variables, Kuhn-Tucker conditions

Module III: Modular Arithmetic 4 hours

  • 1. Introduction to Congruence, Linear congruence, reminder theorem, solving polynomials, system of linear congruence 2. Eluer's theorem, Fermat's little theorem, Application of congruence-RSA algorithm. Self-learning Topics: Divisiblility, GCD, properties of prime numbers, fundamental theorem of arithmetic.

Module IV: Fourier Series 4 hours

  • 1. Dirichlet's conditions, Fourier series of periodic function with period 2π and 2l. 2. Fourier series of even and odd functions. Self-learning Topics: Orthogonal and orthonormal set of functions, Complex form of Fourier Series, Half range Sine and Cosine Series.

Module V: Statistical Techniques 4 hours

  • 1. Karl Pearson's coefficient of correlation (r). 2. Spearman's Rank correlation coefficient (R) (with repeated and non-repeated ranks). 3. Lines of regression, fitting of first-degree curves. Self-learning Topics: Covariance, Fitting of second-degree and exponential curve.

Module VI: Probability 4 hours

  • 1. Moment generating function, Raw moments. 2. Poisson Distribution, Normal Distribution Self-learning Topics: Skewness and Kurtosis of distribution (data), types of distribution and their application.

Module 1

  • Higher Engineering Mathematics, Dr. B. S. Grewal, Khanna Publication.

Module 2

  • Advanced Engineering Mathematics, Erwin Kreyszig, Wiley Eastern Limited.

Module 3

  • Advanced Engineering Mathematics, R. K. Jain and S. R. K. Iyengar, Narosa publication

Module 4

  • Probability, Statistics and Random Processes, T. Veerarajan, Mc. Graw Hill education.

Module 5

  • Number theory, M. G. Nadkarni and J. S. Dani, Tata Mc. Graw Hill education.

Online References

  • Sr. No. Website Name
  • 1 https://nptel.ac.in/courses/111/104/111104085/
  • 2 https://nptel.ac.in/courses/111/106/111106139/
  • 3 https://www.youtube.com/watch?v=2CP3m3EgL1Q
  • 4 https://www.youtube.com/watch?v=Hw8KHNgRaOE
  • 5 https://nptel.ac.in/courses/111/105/111105041/

Reproduced from the University of Mumbai syllabus for B.E. (Artificial Intelligence and Data Science), item 6.20 (N), under NEP 2020, in force from the academic year 2025-26. Wording, module numbering and hours are as printed in that syllabus.

The complete syllabus

This subject is cut from the University circular for its year. Open a document here if you want the whole thing rather than a single subject.

PDF B.E. Artificial Intelligence and Data Science - First Year, Semester I and II - NEP 2020 - Item 7.7 (R-A) NEP 2020, Semesters I and II, in force from 2024-25 Read full PDF Read
PDF B.E. Artificial Intelligence and Data Science - Second Year, Semester III and IV - NEP 2020 - Item 6.20 (N) NEP 2020, Semesters III and IV, in force from 2025-26 Read full PDF Read
PDF B.E. Artificial Intelligence and Data Science - Third Year, Semester V and VI - CBCS REV-2019 C Scheme - Item 6.42 (R) CBCS REV-2019 'C' Scheme, Semesters V and VI, in force from 2022-23 Read full PDF Read
PDF B.E. Artificial Intelligence and Data Science - Fourth Year, Semester VII and VIII - CBCS REV-2019 C Scheme - Item 6.12 (N) CBCS REV-2019 'C' Scheme, Semesters VII and VIII, in force from 2023-24 Read full PDF Read
Report or request
Done!