This course covers the fundamentals of NumPy, a scientific computing library widely used in Python Data Science. The learning outcomes include understanding mathematical, array, and string functions, as well as applications in Linear Algebra, Statistics, and Simulation. The course teaches skills such as creating arrays, data manipulation, universal math operations, and working with various functions. The teaching method includes video tutorials with practical examples. The intended audience for this course is individuals interested in Data Science, Machine Learning, and Python programming.
Overview
Syllabus
Intro.
Creating Arrays.
Data Types.
Slicing & Indexing.
Reshaping Arrays.
Stacking & Splitting.
Copying Arrays.
Universal Math.
Reading From Files.
Statistics Functions.
Creating Formulas.
Trigonometry Functions.
Linear Algebra.
Saving & Loading NumPy Objects.
Loading Libraries in Anaconda.
Financial Functions.
Comparison Functions.
Taught by
Derek Banas
