Ruled

Mathematical Foundation for Computer Application

The mathematics a computer application degree actually runs on — matrices, logic, sets, graphs and numerical methods.

Code
BCA1B01T
Semester
1
Credits
4
Contact
4 hours / week
Modules
5

Modules

Module 1

9 topics

Matrices

From notation to eigenvalues. Every named type of matrix, every standard operation, and every method the exam asks for — worked in full.

  • Definition, order, types of matrices
  • Addition, scalar multiplication and multiplication of matrices
  • Transpose, symmetric and skew-symmetric matrices
  • Determinants and their properties
  • Minors, cofactors, adjoint and inverse
  • Elementary transformations, echelon form and rank
  • Solution of linear equations — Cramer's rule, matrix method, Gauss elimination
  • Eigenvalues, eigenvectors and the Cayley–Hamilton theorem

Open module — 88 solved problems →

Module 2

In preparation

Mathematical Logic

Propositions, connectives, truth tables, tautologies, normal forms, rules of inference and predicate calculus.

  • Propositions and logical connectives
  • Truth tables, tautology and contradiction
  • Logical equivalence and implication
  • Normal forms — CNF and DNF
  • Rules of inference and validity of arguments
  • Predicates and quantifiers
Module 3

In preparation

Set Theory, Relations and Functions

Set operations and Venn diagrams, Cartesian products, types of relations, equivalence classes and functions.

  • Sets, subsets and set operations
  • Venn diagrams and De Morgan's laws
  • Cartesian product and relations
  • Types of relations; equivalence relations and partitions
  • Functions — injective, surjective, bijective; composition and inverse
Module 4

In preparation

Graph Theory

Graphs, degrees, paths and circuits, trees, and the matrix representations that connect back to Module 1.

  • Graphs, vertices, edges and degree
  • Types of graphs; subgraphs and isomorphism
  • Paths, circuits, Euler and Hamiltonian graphs
  • Trees and spanning trees
  • Adjacency and incidence matrices
Module 5

In preparation

Numerical Methods

Solving equations and interpolating data when an exact answer is out of reach.

  • Errors in numerical computation
  • Bisection, Regula Falsi and Newton–Raphson methods
  • Iterative solution of linear systems — Gauss–Seidel
  • Finite differences and interpolation
  • Numerical integration