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# Lecture Zero CSE 333 11 KE117.pptx

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# Lecture Zero CSE 333 11 KE117.pptx

its for lpu student who can easy use this

its for lpu student who can easy use this

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### Lecture Zero CSE 333 11 KE117.pptx

1. 1. Department of Mathematics Lovely Professional University Phagwara, Punjab Dr. Vipin Verma
2. 2. Contents  Course Details  Course Objectives  Text / Reference Books  Course Assessment Model  Course Contents  Learning Outcomes
3. 3. Course Details Course Credits L-T-P : 3-0-0
4. 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. 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. 6. Course Assessment Model  Attendance  CA (Best two out of three tests) : MCQ  MTE : MCQ  ETE : MCQ
7. 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. 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. 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. 10.  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
11. 11.  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
12. 12. Thank You