Udemy – Numerical Analysis & Methods with Python: Theory & Practice 2023-10

Udemy – Numerical Analysis & Methods with Python: Theory & Practice 2023-10 Downloadly IRSpace

Apr 17, 2025 - 20:24 Updated: Aug 17, 2025 - 15:20

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Udemy – Numerical Analysis & Methods with Python: Theory & Practice 2023-10

Numerical Analysis & Methods with Python: Theory & Practice, Explore the fascinating world of numerical methods and unlock the power of Python programming language for solving complex mathematical and physical problems. In this comprehensive course, you will delve into the essential theoretical foundations of numerical analysis while gaining hands-on experience with practical implementations using Python. From root-finding, interpolation and numerical integration to solving differential equations and optimization, this course equips you with the necessary mathematical knowledge and programming skills to tackle a wide range of real-world challenges. You’ll learn to apply numerical algorithms, understand their strengths and limitations, and analyze their accuracy through rigorous error analysis. Designed for both aspiring mathematicians and Python enthusiasts, this course strikes a perfect balance between theory and application. Through engaging lectures, interactive coding exercises, and real-world projects, you’ll build a strong understanding of numerical methods’ underlying principles and learn to implement them effectively with Python libraries like NumPy and SciPy.

What you’ll learn

Foundations of Numerical Methods: Understand the fundamental concepts, principles, and techniques used in numerical analysis.
Mathematical Background: Review essential mathematical foundations required for numerical computations, including calculus and linear algebra.
Root-Finding Methods: Learn various algorithms for finding roots of equations, such as the Bisection method, Newton-Raphson method, and Secant method.
Interpolation and Extrapolation: Lagrange interpolation and Newton’s divided differences.
Ordinary Differential Equations (ODEs): Solve initial value problems of ODEs using numerical techniques like Euler’s method, Runge-Kutta methods (e.g., RK4).
Linear Systems: Learn to solve systems of linear equations using direct methods like Gaussian Elimination, LU decomposition and QR Decomposition.
Linear Systems: Learn to solve systems of linear equations using iterative methods like Jacobi and Gauss-Seidel.
Error Analysis: Understand the sources of error in numerical computations and how to analyze and minimize them
Python Programming: Gain practical experience with Python programming for implementing and solving numerical methods.
Python Libraries: Numpy, SciPy, SymPy

Who this course is for

Students and Academics: Mathematics, engineering, science, and computer science students or professionals seeking to strengthen their understanding of numerical methods and apply them to real-world scenarios.
Python Enthusiasts: Programmers, data scientists, and analysts interested in expanding their Python skills by exploring numerical analysis and its practical applications.
Anyone Interested in Mathematics and Coding

Specificatoin of Numerical Analysis & Methods with Python: Theory & Practice

Publisher : Udemy
Teacher : Mohamed Essadki
Language : English
Level : All Levels
Number of Course : 90
Duration : 14 hours and 12 minutes

Content of Numerical Analysis & Methods with Python: Theory & Practice

Numerical Analysis & Methods with Python_ Theory & Practice

Requirements

You should have a basic background in algebra and calculus (derivative, integration,..), in addition some basic programming experiences
Programming Basics: While the course will cover Python programming, some prior programming experience or familiarity with programming concepts would be helpful
It’s essential for students to have access to a text editor or an Integrated Development Environment (IDE) to write and execute Python code