This course covers advanced topics in NumPy and SciPy, focusing on broadcasting rules, strides, stride tricks, and advanced indexing. By the end of the course, learners will be able to apply these concepts effectively in array computing. The teaching method involves a hands-on tutorial approach, with practical exercises to reinforce learning. The course is designed for individuals comfortable with Python syntax and with some prior experience in NumPy or array computing.
Overview
Syllabus
Introduction
Jupiter Notebook
Gene Expression
Expression Data
NumPy Array
Reads per kilobase
RAM
Transpose
Slicing
Exercises
Variance
Broadcasting
Taught by
Enthought
