Numpy - The Complete Guide

What you'll learn
Learn concepts of Numpy as a foundation for other data science libraries
Import and manipulate large datasets using NumPy
Perform complex numerical tasks efficiently using Numpy Arrays
Requirements
be conmfortable with basic concepts of Python
zeal and enthusiasm to learn
Description
Welcome to the most comprehensive course on the NumPy library of Python! This complete guide on Numpy helps you take your Python skills to the next level. At the end of the course, you shall have gained enough expertise in the Numpy library so as to venture into the field of data driven technologies which are hot and trending - data science, data analysis, and machine learning.Numpy, or Numerical Python, works under the hood; is the backbone of many other Python libraries. Pandas, ScikitLearn, SciPy, Tkinter, Matplotlib - they all are built on top of NumPy; So, if you know NumPy well, you will find it easy to explore these libraries of data science and data analysis and can join the hottest skill of the century: Data Science & Machine Learning. And don't you worry! In this course, we'll cover every nooks and crannies the Numpy library offers. You won't find such an elaborate tutorial on Numpy on Udemy, for sure! Intended for absolute beginners who know Python , and want to venture into data science and machine learning, but don't know where to start, the course covers complete details of every important concept of Numpy, includingWhat is NumPy,Where it is usedHow and why it works with numbers so easilyConcept of numerical arraysCreating arraysInsert, update and delete Numpy arraysArray manipulation using NumpyImportant functions (methods) in NumpyLinear algebra with NumpyYou also get the opportunity to apply your newly-learned Numpy skills and knowledge of Python, on practical projects. All this and more in the course!This course is still in a draft mode. I am still adding more and more content, quiz, projects related to data processing with different functionalities of Numpy. So stay tuned and enroll now.
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 Installation: NumPy with Python (Anaconda)
Section 2: Exploring Numpy
Lecture 3 Opening Notebook and importing NumPy
Lecture 4 How to create Numpy arrays
Lecture 5 Exploring the array() method
Lecture 6 Visualize the dimensions of a numpy array
Lecture 7 List vs. Array - memory wise!
Lecture 8 List vs. Array - performance wise!
Section 3: Creating Numpy arrays
Lecture 9 Broadcasting - overview
Lecture 10 Numpy arrays attributes - shape, size, and ndim
Lecture 11 Array creation methods - overview
Lecture 12 Array creation methods - zeros() & ones()
Lecture 13 Array creation method - arange()
Lecture 14 Array creation methods - continued
Section 4: Accessing numpy arrays - indexing and sicing
Lecture 15 Indexing in Numpy
Lecture 16 Slicing in Numpy
Section 5: Manipulating Numpy arrays
Lecture 17 manipulating array's properties - ndim, shape and size
Lecture 18 method chaining
Section 6: Arithmetic operations between arrays
Lecture 19 Arithmetic operations & Broadcasting explained
Beginner Python developer who are curious about data science


Homepage

https://www.udemy.com/course/numpy-python-the-complete-guide/