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This course format through pre-recorded video. You can buy and watch it to learn at any time.
This course assumes a strong foundation in calculus, linear algebra, and basic programming skills. Prior exposure to mathematical modeling and differential equations is beneficial but not mandatory.
By the end of this course, students should be able to:
- Apply numerical methods to solve a wide range of engineering and scientific problems.
- Analyze the accuracy and stability of numerical algorithms.
- Implement numerical solutions using programming languages like MATLAB, Python, or C/C++.
- Prepare for GATE examinations by mastering the numerical methods portion of the syllabus.
This course is designed to help students not only excel in their GATE exams but also to develop practical problem-solving skills that are highly valuable in engineering and scientific research and practice.
This course is designed to equip students with the fundamental concepts and techniques of numerical methods, which are essential for solving engineering and scientific problems. The course focuses on both theoretical understanding and practical implementation of numerical algorithms. It is tailored to meet the requirements of GATE examinations in various engineering disciplines.
Roots of Algebraic Equations (29 min)
Descartes' Rule of Signs (22 min)
Bisection method & Regula - Falsi method (False Position Method) (22 min)
Newton Raphson Method (20 min)
Example (Bisection Method & Regula Falsi Method) (30 min)
Example (Newton Raphson Method) (26 min)
Example (Newton Raphson Method) (21 min)
Previous Year Example-I (20 min)
Previous Year Example-II (24 min)
Finite Differences (34 min)
Backward Differences (42 min)
Newton Gregory formula for interpolation using backward differences (27 min)
Gental Differences (14 min)
Gaussian & Sterling’s interpolation formulae (65 min)
Numerical Integration (62 min)
Simpson 1/3rd rule and 3/8th rule (58 min)
Gauss Siedel Method (50 min)
Example (28 min)
Euler method (44 min)
Runge Kutta method (54 min)
Error Analysis Method in Numerical Method (44 min)
Basic Error Principle (53 min)
Convergence of Newton Method (44 min)
The Graduate Aptitude Test in Engineering (GATE) is a competitive examination in India for students seeking admission to postgraduate programs in various engineering and science disciplines. Numerical Methods may be a part of the syllabus for certain GATE papers, such as Computer Science and Engineering, Mechanical Engineering, Civil Engineering, and others, depending on the specific paper's syllabus.
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Roots of Algebraic Equations :
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Bisection Method & Regula Falsi Method :
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Example-(Bisection Method & Regula Falsi Method) :
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