Engineering Mathematics - Numerical Analysis

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Course type: Online Instructor led Course

Platform: Google+ hangout,skype,facebook video call,

Course ID: 24904

Course type: Online Instructor led Course

Platform: Google+ hangout,skype,facebook video call,

No Reviews Yet

Date and Time

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Sujoy Krishna Das picture
Sujoy Krishna Das

Engineer & Educator

About Sujoy Krishna Das

More than 2 years of experience of online tutoring and educational content creation.
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About the Course

Numerical Analysis, also known as- Numerical Methods and Statistics; is a subject which is taught in engineering disciplines, management studies and in B.Sc Math Honours. Do you know you can solve many real life problems easily if you know Numerical Methods? It's a very interesting subject and is quite easy too if you can understand it!
In this tutorial the tutor will explain almost all Numerical Methods topics you ever need to pass your exam! He'll tell you how to solve them easily step-by-step and will you give you many shortcut tips so that sometimes you can directly get the answer without doing the whole math!

Topics Covered

I'll cover the following methods-
I) Solving Algebraic and Transcendental Equations
1. Iteration Method
2. Bisection Method
3. Regula Falsi Method
4. Newton Raphson Method
5. Secant Method
II) Solving Simultaneous Linear Equations
6. Solving Simultaneous Equations (using Casio fx-991ES Scientific Calculator)
7. Gauss Elimination
8. Gauss Jordan Elimination
9. Gaussian Compact Scheme
10. Matrix Inverse using different techniques
11. Gauss Seidel Iteration Method
12. Gauss Jacobi Iteration Method
13. Solving System of Linear Eqations by Adjoint Method
III) Finding Eigen Values and Eigen Vectors of a Matrix
14. Finding Largest & Least Eigen Value of a Matrix
15. Sum & Product of Eigen Values & Eigen Vectors
IV) Numerical Interpolation
16. Lagrange Interpolation
17. Inverse Interpolation
18. Newton Forward Interpolation
19. Newton Backward Interpolation
20. Newton Divided Difference Interpolation
V) Numerical Solutions of Ordinary Differential Equations
21. Runge-Kutta Method
22. Euler's Method
23. Adams Bashforth Predictor Corrector Method
24. Milne's Predictor-Corrector Method
25. Taylor Series Method
VI) Numerical Integration
26. Simpson's 1/3 Rule + finding value of Pi
27. Simpson's 3/8 Rule
28. Trapezoidal Rule
VII) Matrix Algebra
29. Properties of Matrices with Proof
30. Properties of Determinants with Proof - Part 1
31. Properties of Determinants with Proof - Part 2
32. How to find Adjoint of a matrix
33. How to find Determinant of 3x3, 4x4, 5x5 Matrix
34. Matrix Inverse by Adjoint Method
35. Matrix Inverse by Gauss-Jordan Method

Who should attend

Anyone having any of the following subjects in their syllabus-
1. Numerical Analysis
2. Numerical Methods and Statistics
3. Discrete Mathematics
4. Matrix Algebra
5. Engineering Mathematics
6. Mathematics for Management
7. Matrix Algebra
8. Linear Programming Problems (LPP)



What you need to bring


Key Takeaways

Deep understanding of concepts with confidence to solve problems all by yourself. And lots of shortcut techniques to solve the math quickly, sometimes even without doing the math!


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