A Beginner Guide to Numerical Methods in MATLAB
- Development
- Nov 27, 2024

A Beginners Guide to Numerical Methods in MATLAB, available at $44.99, has an average rating of 3.85, with 36 lectures, 11 quizzes, based on 95 reviews, and has 733 subscribers.
You will learn about Understand about the ways computer store numbers Choose the right numerical methods to solve a problem Measure (and avoid) the errors inherent in numeric calculations See how algorithms are implemented in MATLAB This course is ideal for individuals who are This course is designed for anyone interested in the numerical methods and their applications for solving real-world problems or Engineers, computer scientists, mathematicians and finance people will enjoy this course It is particularly useful for This course is designed for anyone interested in the numerical methods and their applications for solving real-world problems or Engineers, computer scientists, mathematicians and finance people will enjoy this course.
Enroll now: A Beginners Guide to Numerical Methods in MATLAB
Summary
Title: A Beginners Guide to Numerical Methods in MATLAB
Price: $44.99
Average Rating: 3.85
Number of Lectures: 36
Number of Quizzes: 11
Number of Published Lectures: 36
Number of Published Quizzes: 11
Number of Curriculum Items: 47
Number of Published Curriculum Objects: 47
Original Price: $39.99
Quality Status: approved
Status: Live
What You Will Learn
Who Should Attend
Target Audiences
This course is about?Numerical Methods and covers some of the popular methods and approaches being used daily by mathematicians and everyone involved in computation.
This course will teach you about
This course consists of the following materials:
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Chapter 2: Machine Representation of Numbers
Lecture 1: Base 2 Representation
Lecture 2: Floating-Point Representation
Lecture 3: Machine Epsilon
Lecture 4: Round-Off and Truncation Errors
Chapter 3: Basic Concepts
Lecture 1: Function Continuity
Lecture 2: Rolles Theorem
Lecture 3: First Mean Value Theorem
Lecture 4: Bolzanos Theorem
Chapter 4: One-Point Iterative Methods
Lecture 1: Introduction
Lecture 2: Convergence
Lecture 3: Acceleration of Convergence
Lecture 4: Order of Convergence
Lecture 5: Newtons Method (a.k.a. Newton-Raphson)
Lecture 6: Multidimensional Extensions of Newtons Method
Lecture 7: Approximate Newtons Method
Lecture 8: Horners Algorithm for Polynomial Equations
Chapter 5: Two-Point Iterative Methods
Lecture 1: Bisection Method
Lecture 2: Regula Falsi Method
Lecture 3: Secant Method
Chapter 6: Interpolation and Curve Fitting
Lecture 1: Polynomial Interpolation
Lecture 2: Newton Basis
Lecture 3: Divided Differences
Lecture 4: Divided Differences: Examples
Lecture 5: Forward Differences
Lecture 6: Lagrangian Interpolation
Lecture 7: Nevilles Algorithm
Chapter 7: Differentiation
Lecture 1: First Derivative Approximations
Lecture 2: Second Derivative Approximations
Lecture 3: Error Terms by Taylor Series Expansion
Lecture 4: Richardson Interpolation
Chapter 8: Integration (Quadrature)
Lecture 1: Introduction
Lecture 2: Trapezium Rule
Lecture 3: Midpoint Rule
Lecture 4: Gauss-Hermite
Lecture 5: Gauss-Laguerre
Instructors

Dmitri Nesteruk
Software/Hardware Engineering ? Quant Finance ? Algotrading

Xenia Kuznetsova
Web developer
Rating Distribution
Frequently Asked Questions
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