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Department of Mathematics
Lovely Professional University
Phagwara, Punjab
Dr. Vipin Verma
Contents
 Course Details
 Course Objectives
 Text / Reference Books
 Course Assessment Model
 Course Contents
 Learning Outcomes
Course Details
Course Credits
L-T-P : 3-0-0
Course Objectives
 Practice all the mathematical theories and concepts
important for a computer science engineer.
 Identify the utility of mathematics in higher studies.
 Score good marks in higher studies related competitive
exam like GATE..
 Evaluate different mathematical theories related to
Discrete Mathematics, Linear Algebra, Calculus, and
Probability.
Books
Text Book
 DISCRETE MATHEMATICS AND ITS APPLICATIONS WITH
COMBINATORICS AND GRAPH THEORY by KENNETH H.
ROSEN, Mc Graw Hill Education
 ADVANCED ENGINEERING MATHEMATICS by R K JAIN,
NAROSA PUBLISHING HOUSE
Reference Books
 ENGINEERING MATHEMATICS II by T VEERARAJAN, Mc
Graw Hill Education
 FUNDAMENTALS OF MATHEMATICAL STATISTICS by
GUPTA S.C. , KAPOOR V.K., SULTAN CHAND & SONS (P)
LTD.
Course Assessment Model
 Attendance
 CA (Best two out of three tests) : MCQ
 MTE : MCQ
 ETE : MCQ
Course Contents
 Discrete Mathematics : propositional logic, first order logic, sets,
relations, functions, partial orders, lattices, groups
 Graphs : connectivity, matching, coloring Combinatorics :
counting, recurrence relations, generating functions
 Linear Algebra : matrices, determinants, system of linear
equations, eigenvalues, eigenvectors, LU decomposition
 Calculus : limits, continuity, differentiability, maxima and
minima, mean value theorem, integration
 Probability : random variables, uniform, normal, exponential,
Poisson and binomial distributions, mean, median, mode,
standard deviation, conditional probability, Bayes theorem
 Numerical Ability : numerical computation, numerical
estimation, numerical reasoning, data interpretation
Learning Outcomes
On successful completion of the course, the students
should be able to:
 Understand the Relations and their properties,
Equivalence relations, Partial ordering relations,
Lattice, Sub lattice
 Understand and able to apply the concepts of Graph
theory in real life application
 Understand and able to apply the concepts of Matrices
 Understand and able to apply the concepts of
probability distribution.
A set is an unordered collection of objects, called
elements or members of the set.
A set is said to contain its elements. We write a ∈ A to
denote that a is an element of the set A. The notation a ∈
A denotes that a is not an element of the set A.
 Q 1 If A and B are sets and A∪ B= A ∩ B, then
 A. A = Φ
 B. B = Φ
 C. A = B
 D. none of these
 Q2. If X and Y are two sets, then the compliment of
 X ∩ (Y ∪ X) equals
 A. X
 B. Y
 C. Ø
 D. None of these
Thank You

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Lecture Zero CSE 333 11 KE117.pptx

  • 1. Department of Mathematics Lovely Professional University Phagwara, Punjab Dr. Vipin Verma
  • 2. Contents  Course Details  Course Objectives  Text / Reference Books  Course Assessment Model  Course Contents  Learning Outcomes
  • 4. Course Objectives  Practice all the mathematical theories and concepts important for a computer science engineer.  Identify the utility of mathematics in higher studies.  Score good marks in higher studies related competitive exam like GATE..  Evaluate different mathematical theories related to Discrete Mathematics, Linear Algebra, Calculus, and Probability.
  • 5. Books Text Book  DISCRETE MATHEMATICS AND ITS APPLICATIONS WITH COMBINATORICS AND GRAPH THEORY by KENNETH H. ROSEN, Mc Graw Hill Education  ADVANCED ENGINEERING MATHEMATICS by R K JAIN, NAROSA PUBLISHING HOUSE Reference Books  ENGINEERING MATHEMATICS II by T VEERARAJAN, Mc Graw Hill Education  FUNDAMENTALS OF MATHEMATICAL STATISTICS by GUPTA S.C. , KAPOOR V.K., SULTAN CHAND & SONS (P) LTD.
  • 6. Course Assessment Model  Attendance  CA (Best two out of three tests) : MCQ  MTE : MCQ  ETE : MCQ
  • 7. Course Contents  Discrete Mathematics : propositional logic, first order logic, sets, relations, functions, partial orders, lattices, groups  Graphs : connectivity, matching, coloring Combinatorics : counting, recurrence relations, generating functions  Linear Algebra : matrices, determinants, system of linear equations, eigenvalues, eigenvectors, LU decomposition  Calculus : limits, continuity, differentiability, maxima and minima, mean value theorem, integration  Probability : random variables, uniform, normal, exponential, Poisson and binomial distributions, mean, median, mode, standard deviation, conditional probability, Bayes theorem  Numerical Ability : numerical computation, numerical estimation, numerical reasoning, data interpretation
  • 8. Learning Outcomes On successful completion of the course, the students should be able to:  Understand the Relations and their properties, Equivalence relations, Partial ordering relations, Lattice, Sub lattice  Understand and able to apply the concepts of Graph theory in real life application  Understand and able to apply the concepts of Matrices  Understand and able to apply the concepts of probability distribution.
  • 9. A set is an unordered collection of objects, called elements or members of the set. A set is said to contain its elements. We write a ∈ A to denote that a is an element of the set A. The notation a ∈ A denotes that a is not an element of the set A.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.  Q 1 If A and B are sets and A∪ B= A ∩ B, then  A. A = Φ  B. B = Φ  C. A = B  D. none of these
  • 21.
  • 22.  Q2. If X and Y are two sets, then the compliment of  X ∩ (Y ∪ X) equals  A. X  B. Y  C. Ø  D. None of these