MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 34 Lectures ( 7h 7m ) | Size: 2.84 GB
All you need to know about numerical methods and their implementation is covered.
What you'll learn:
Understand the significance of numerical methods in solving mathematical problems.
Learn the principles of the bisection method for solving non-linear equations.
Understand how to apply the bisection method to find roots of equations.
Explore the Newton Raphson method for finding roots of non-linear equations.
Understand techniques for solving systems of non-linear equations.
Comprehend the concept of linear systems and their representation.
Learn LU decomposition as a method for solving linear equations.
Gain proficiency in fitting curves to given data sets.
Learn the principles of polynomial regression and its applications.
Explore various interpolation methods, including Lagrangian and Newtonian interpolation.
Understand numerical techniques for approximating derivatives.
Learn different numerical integration techniques, including Trapezoidal Rule, Simpson's Rule, Simpson's 3/8th Rule, and Gauss Quadrature Rule.
Understand and implement various numerical methods for solving ODEs.
Learn the finite difference method for solving boundary value problems.
Apply numerical techniques to solve BVPs in practical scenarios.
Requirements:
Mathematical Background: Familiarity with basic mathematical concepts such as algebra and calculus is recommended. Understanding equations, derivatives, and integrals will enhance the learning experience.
Programming Knowledge (Optional): While not mandatory, a basic understanding of programming concepts can be advantageous. The course may involve implementing numerical algorithms in languages such as Python or MATLAB. However, detailed explanations and examples will be provided, making it beginner-friendly.
Curiosity and Enthusiasm: A willingness to explore and experiment with numerical methods is crucial. The course is designed to be engaging, and a curious mindset will contribute to a more enriching learning experience.
Desire to Apply Knowledge: The course focuses on practical applications of numerical methods. Learners should be motivated to apply the concepts learned to solve real-world problems in various domains.
