NumPy, SciPy, and Matplotlib Recipes

NumPy, SciPy, and Matplotlib Recipes, available at $69.99, has an average rating of 4.1, with 100 lectures, based on 34 reviews, and has 239 subscribers.

You will learn about Understand and explain the Scientific Ecosystem Work with Ndarrays in NumPy Mathematical and Statistical Functions Image Processing with NumPy and Matplotlib Basic and Advanced Visualizations using Matplotlib SciPy, NumPy, and Matplotlib Recipes K-Means Clustering This course is ideal for individuals who are Data Science and Machine Learning Professionals or Computer Vision Professionals or Raspberry Pi Enthusiasts or Anyone with zeal and enthusiasm to learn It is particularly useful for Data Science and Machine Learning Professionals or Computer Vision Professionals or Raspberry Pi Enthusiasts or Anyone with zeal and enthusiasm to learn.

Enroll now: NumPy, SciPy, and Matplotlib Recipes

Summary

Title: NumPy, SciPy, and Matplotlib Recipes

Price: $69.99

Average Rating: 4.1

Number of Lectures: 100

Number of Published Lectures: 100

Number of Curriculum Items: 100

Number of Published Curriculum Objects: 100

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Understand and explain the Scientific Ecosystem
Work with Ndarrays in NumPy
Mathematical and Statistical Functions
Image Processing with NumPy and Matplotlib
Basic and Advanced Visualizations using Matplotlib
SciPy, NumPy, and Matplotlib Recipes
K-Means Clustering

Who Should Attend

Data Science and Machine Learning Professionals
Computer Vision Professionals
Raspberry Pi Enthusiasts
Anyone with zeal and enthusiasm to learn

Target Audiences

Data Science and Machine Learning Professionals
Computer Vision Professionals
Raspberry Pi Enthusiasts
Anyone with zeal and enthusiasm to learn

Become a Master in Scientific Python and acquire employers’ one of the most requested skills of 21st Century! A great Scientific Python programmer earns more than $150000 per year.

This is the most comprehensive, yet straight-forward course for the Scientific Python on Udemy! Whether you have never used SciPy before, already know basics of Python, or want to learn the advanced features of NumPy with Python 3, this course is for you! In this course we will teach you NumPy, SciPy, Matplotlib, and Jupyter Notebook.

With over 100 lectures and more than 10 hours of video this comprehensive course leaves no stone unturned in teaching you Scientific Python!

This course will teach you Scientific Python in a very practical manner, with every lecture comes a full Python 3 programming video and a corresponding Jupyter notebook that has Python 3 code! Learn in whatever manner is the best for you!

We will start by helping you get Python3, NumPy, Matplotlib, Jupyter, and SciPy installed on your Windows computer and Raspberry Pi.

We cover a wide variety of topics, including:

Basics of Scientific Python Ecosystem
Basics of SciPy, NumPy, and Matplotlib
Installation of Python 3 on Windows
Setting up Raspberry Pi
Tour of Python 3 environment on Raspberry Pi
Jupyter installation and basics
Ndarrays
Array Creation Routines
Basic Visualization with Matplotlib
Ndarray Manipulation
Installation of SciPy
Image Processing with NumPy and Matplotlib
NumPy and SciPy
Scientific and Business Visualizations
K-Means clustering with SciPy

You will get lifetime access to over 100 lectures plus corresponding PDFs and the Jupyter notebooks for the lectures!

So what are you waiting for? Learn SciPy, NumPy, and Matplotlib in a way that will advance your career and increase your knowledge, all in a fun and practical way!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Objectives, Prerequisites, and Audiences

Lecture 2: Contents and Topics Overview

Lecture 3: Please leave your feedback

Lecture 4: Scientific Python Ecosystem

Lecture 5: Introduction to NumPy

Lecture 6: Important Projects in scientific Python Ecosystem

Chapter 2: Python 3 on Windows

Lecture 1: Installation

Lecture 2: Verification

Chapter 3: Raspberry Pi and Python

Lecture 1: Single Board Computers and Raspberry Pi

Lecture 2: Installing Raspberry Pi OS

Lecture 3: Remote connection with VNC

Lecture 4: Install IDLE3 on Raspberry Pi Raspbian

Lecture 5: Python on Raspberry Pi

Lecture 6: Additional software for remote connection

Lecture 7: Turn your Raspberry Pi 4 into a portable Tablet with Sunfounder Raspad 3

Chapter 4: Python 3 Basics

Lecture 1: "Hello World" on Windows!

Lecture 2: "Hello World" on Raspberry Pi!

Lecture 3: Interpreter vs Script Mode

Lecture 4: IDLE

Lecture 5: RPi vs PC

Chapter 5: Python Package Index and pip

Lecture 1: Python Package Index

Lecture 2: pip on Windows

Lecture 3: pip3 on Raspberry Pi

Chapter 6: Install NumPy and Matplotlib

Lecture 1: Install NumPy and Matplotlib on Windows

Lecture 2: Install NumPy and Matplotlib on Raspberry Pi

Chapter 7: IPython and Jupyter Basics

Lecture 1: IPython and Jupyter

Lecture 2: Install Jupyter on Windows

Lecture 3: Install Jupyter on Raspberry Pi

Lecture 4: PuTTY

Lecture 5: Connect to a remote Jupyter Notebook

Lecture 6: A brief Tour of Jupyter

Lecture 7: Commands used in this Section

Chapter 8: Getting Started with NumPy

Lecture 1: Ndarray, Indexing, and Slicing

Lecture 2: Ndarray Properties

Lecture 3: NumPy constants

Lecture 4: NumPy Datatypes

Chapter 9: Creation of arrays and Matplotlib

Lecture 1: Ones and Zeros

Lecture 2: Matrices

Lecture 3: Introduction to Matplotlib

Lecture 4: Visualize Numerical Ranges

Chapter 10: NumPy and Random

Lecture 1: NumPy and Random

Chapter 11: Array manipulation

Lecture 1: Array manipulation

Chapter 12: Bitwise Operations

Lecture 1: Bitwise Operations

Chapter 13: Statistical Routines

Lecture 1: Statistical Routines

Chapter 14: FFTs

Lecture 1: FFTs

Lecture 2: Advanced FFTs

Chapter 15: Linear Algebra

Lecture 1: Dot Products

Lecture 2: Vector Dot product

Lecture 3: Inner Product

Lecture 4: QR Decomposition

Lecture 5: Determinants and Solving Linear Equations

Chapter 16: Mathematical and Trigonometric Function

Lecture 1: Trigonometric Functions

Lecture 2: Hyperbolic Functions

Lecture 3: Exponential Functions

Lecture 4: Logarithmic Functions

Lecture 5: Convolution

Chapter 17: Image Processing and Matplotlib

Lecture 1: What is Digital Image Processing?

Lecture 2: Image Datasets

Lecture 3: Pillow Installation

Lecture 4: Read, display, and save images with Matplotlib

Lecture 5: NumPy for Images

Lecture 6: Image Statistics

Lecture 7: Image Masks

Lecture 8: Image Channels

Lecture 9: Arithmetic Operations

Lecture 10: Logical Operations

Lecture 11: Histogram with NumPy and Matplotlib

Chapter 18: File Operations with NumPy

Lecture 1: NumPy File Format

Lecture 2: Reading CSV File

Chapter 19: Set Operations

Lecture 1: Set Operations

Chapter 20: Sorting and Counting

Lecture 1: Sorting Routines

Lecture 2: Counting Non Zero Elements

Chapter 21: Plotting in detail

Lecture 1: Single Line Plot

Lecture 2: Multiline Plot

Lecture 3: Grid, Axes, and Labels

Lecture 4: Colors, Lines, and Markers

Chapter 22: Introduction to SciPy

Lecture 1: Introduction to SciPy

Lecture 2: Install SciPy on Windows

Instructors

Ashwin Pajankar • 85,000+ Students Worldwide
Instructor | Programmer | Maker | Author | Youtuber

Rating Distribution

1 stars: 0 votes
2 stars: 2 votes
3 stars: 6 votes
4 stars: 9 votes
5 stars: 17 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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