Learn Python & Numpy with simple videos
What you'll learn
Understanding Python Numpy basics in just 1.5 hours
Understanding Lists are different from arrays
Implementing array operations using Numpy module in python
Searching and sorting operations in Arrays
Requirements
Python Programming
Description
NumPy is a basic level external library in Python used for complex mathematical operations. NumPy overcomes slower executions with the use of multi-dimensional array objects. It has built-in functions for manipulating arrays. We can convert different algorithms to can into functions for applying on arrays. NumPy has applications that are not only limited to itself. It is a very diverse library and has a wide range of applications in other sectors. Numpy can be put to use along with Data Science, Data Analysis and Machine Learning. It is also a base for other python libraries. These libraries use the functionalities in NumPy to increase their capabilities.This course introduce with all majority of concept of NumPy - numerical python library.You will learn following topics :1) Creating Arrays using Numpy in Python2) Accessing Arrays using Numpy in Python3) Finding Dimension of the Array using Numpy in Python4) Negative Indexing on Arrays using Numpy in Python5) Slicing an Array using Numpy in Python6) Checking Datatype of an Array using Numpy in Python7) Copying an Array using Numpy in Python8) Iterating through arrays using Numpy in Python9) Shape of Arrays using Numpy in Python10) Reshaping Arrays using Numpy in Python11) Joining Arrays using Numpy in Python12) Splitting Array using Numpy in Python13) Sorting an Array using Numpy in Python14) Searching in Array using Numpy in Python15) Filtering an Array using Numpy in Python16) Generating a Random Array using Numpy in PythonArrays in Numpy are equivalent to lists in python. Like lists in python, the Numpy arrays are homogenous sets of elements. The most important feature of NumPy arrays is they are homogenous in nature. This differentiates them from python arrays. It maintains uniformity for mathematical operations that would not be possible with heterogeneous elements. Another benefit of using NumPy arrays is there are a large number of functions that are applicable to these arrays. These functions could not be performed when applied to python arrays due to their heterogeneous nature.Happy learningSurendra Varma Pericherla
Overview
Section 1: Understanding Lists are different from Numpy arrays
Lecture 1 Creating & Accessing Listsin Python
Lecture 2 Working with built-in functions in Lists
Section 2: Functions in Python
Lecture 3 Functions
Lecture 4 Examples on Functions
Section 3: Using Numpy Module in Python
Lecture 5 Online IDE for running Python Numpy programs
Lecture 6 Creating & Accessing elements in 1D Array
Lecture 7 Creating & Accessing elements in 2D Array
Lecture 8 Finding Dimension of the Array
Lecture 9 Using Negative Indexing to access elements in 1D array
Lecture 10 Using Negative Indexing to access elements in 2D array
Lecture 11 Slicing an Array
Lecture 12 Checking Datatype of an Array
Lecture 13 Copy Operation on an array
Lecture 14 Iterating 1D array
Lecture 15 Iterating 2D array
Lecture 16 Finding Shape of the Array
Lecture 17 Reshaping 1D Array to 2D Array
Lecture 18 Joining Two Arrays
Lecture 19 Splitting an Array
Lecture 20 Sorting an Array
Lecture 21 Searching for an Element in Array
Lecture 22 Filtering an Array
Lecture 23 Generate a Random Integer
Lecture 24 Generating a Random Array
Section 4: Quizzes
Lecture 25 Question 1
Lecture 26 Solution to Question 1
Lecture 27 Question 2
Lecture 28 Solution to Question 2
Lecture 29 Question 3
Lecture 30 Solution to Question 3
Lecture 31 Question 4
Lecture 32 Solution to Question 4
Lecture 33 Question 5
Lecture 34 Solution to Question 5
Lecture 35 Question 6
Lecture 36 Solution to Question 6
Engineering Students, Software Developers And Aspiring Data Scientists
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