Numerical Python or Numpy is an important library when it comes to performing complex computation. In this course, we deep dive into Numpy starting with basic concepts, explaining what , why and motivations for creating such library to advanced concepts. This course can be a pathway towards becoming a data scientist.

In this course you will start with basic introduction to Numpy, how this course is designed to accommodate needs for new world requirement of data science. From there you will get introduction to tools needed to be successful in learning Numpy. Before we go into details about the technology we will travel back to memory lane and see where this idea originated from.

This course will cover NDArray and their operations, matrix multiplication and its use cases. We will talk about increment and decrement operators, indexing, slicing and iterating over arrays which are crucial aspect of data wrangling and data clean up part.

Further, we will learn conditional expressions, shape, and array manipulation while applying universal functions. You will learn role broadcasting plays in Numpy space.

We will learn I/O operations like loading, saving, reading and read loading files also we will look at how Numpy manages memory so you can work with data more efficiently.