Dive into a comprehensive 93-minute tutorial on NumPy tailored for physicists, engineers, and mathematicians. Learn essential array operations, indexing and slicing techniques, and apply calculus and statistics concepts using NumPy. Explore multi-dimensional arrays and their functions, delve into linear algebra topics including matrix operations, systems of equations, and eigenvalue problems. Gain practical experience through numerous examples and discover how to work with basic datasets. Access accompanying code on GitHub and enhance your Python skills for STEM applications.
Overview
Syllabus
Introduction
Array Operations
Indexing and Slicing 1 Dimension
Calculus and Statistics
Examples
Multi-Dimensional Arrays
Functions on Multi-Dimensional Arrays
Linear Algebra: Matrix Operations
Linear Algebra: Systems of Equations
Linear Algebra: Eigenvalue Problems
Examples
Basic Datasets
Taught by
Mr. P Solver
