HOT
blank

Master Scientific Computing in Python with NumPy

Development

Rating4.4
Enroll Now

Master Scientific Computing in Python with NumPy, available at $79.99, has an average rating of 4.4, with 74 lectures, 23 quizzes, based on 194 reviews, and has 1443 subscribers.

You will learn about Learn to confidently work with vectors and matrices in NumPy. Learn basic functionality like sorting, calculating means, and finding max/min values. Learn to draw line plots, bar plots, and scatterplots. Learn to generate different types of random vectors. Learn to modify and reshape matrices to your advantage. Learn Boolean indexing and advanced slicing to extract useful information. Learn to do basic linear algebra in NumPy like solving linear systems, calculating inverses, and more! Get an understanding of how ndarrays work and utilize this to create fast code. Learn Fourier transforms with NumPy and use this to manipulate images and audio. Learn advanced linear algebra like the QR decomposition and partial least squares. Learn how to preserve your NumPy objects in different formats. Learn about neighboring libraries and that NumPy is used everywhere in Python's data science stack. This course is ideal for individuals who are Anyone who wants to get a good understanding of NumPy. or Students who want to implement topics like linear algebra, machine learning, and image processing in Python. or Python developers who are curious about NumPy and data science! It is particularly useful for Anyone who wants to get a good understanding of NumPy. or Students who want to implement topics like linear algebra, machine learning, and image processing in Python. or Python developers who are curious about NumPy and data science!.

Enroll now: Master Scientific Computing in Python with NumPy

Summary

Title: Master Scientific Computing in Python with NumPy

Price: $79.99

Average Rating: 4.4

Number of Lectures: 74

Number of Quizzes: 23

Number of Published Lectures: 74

Number of Published Quizzes: 23

Number of Curriculum Items: 97

Number of Published Curriculum Objects: 97

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

  • Learn to confidently work with vectors and matrices in NumPy.
  • Learn basic functionality like sorting, calculating means, and finding max/min values.
  • Learn to draw line plots, bar plots, and scatterplots.
  • Learn to generate different types of random vectors.
  • Learn to modify and reshape matrices to your advantage.
  • Learn Boolean indexing and advanced slicing to extract useful information.
  • Learn to do basic linear algebra in NumPy like solving linear systems, calculating inverses, and more!
  • Get an understanding of how ndarrays work and utilize this to create fast code.
  • Learn Fourier transforms with NumPy and use this to manipulate images and audio.
  • Learn advanced linear algebra like the QR decomposition and partial least squares.
  • Learn how to preserve your NumPy objects in different formats.
  • Learn about neighboring libraries and that NumPy is used everywhere in Python's data science stack.

Who Should Attend

  • Anyone who wants to get a good understanding of NumPy.
  • Students who want to implement topics like linear algebra, machine learning, and image processing in Python.
  • Python developers who are curious about NumPy and data science!

Target Audiences

  • Anyone who wants to get a good understanding of NumPy.
  • Students who want to implement topics like linear algebra, machine learning, and image processing in Python.
  • Python developers who are curious about NumPy and data science!

Do you want to learn NumPy and get started with data analysis in Python? This course is both a comprehensive and hands-on introduction to NumPy!

What this course is all about:

In this course, we will teach you the ins and outs of the Python library NumPy. This library is incredibly powerful and is used for scientific computing, linear algebra, image processing, machine learning, and more. If you are interested in one of these topics or simply want to get started with data science in Python, then this is the course for you!

The course will teach you everything you need to know to professionally use NumPy. We will start with the basics, and then gradually move on to more complicated topics. As NumPy is the fundamental building block for other popular Python libraries like Pandas, Scikit-Learn, and PyTorch, it’s a great library to get you started with data science in Python.

Why choose us?

This course is a comprehensive introduction to NumPy! We don’t shy away from the technical stuff and want you to stand out with your newly learned NumPy skills.

The course is filled with carefully made exercises that will reinforce the topics we teach. In between videos, we give small exercises that help you reinforce the material. Additionally, we have larger exercises where you will be given a Jupiter Notebook sheet and asked to solve a series of questions that revolve around a single topic. We give exercises on awesome topics like audio processing, linear regression, and image manipulation!

We’re a couple (Eirik and Stine) who love to create high-quality courses! In the past, Eirik has taught both Python and NumPy at the university level, while Stine has written learning material for a university course that has used NumPy. We both love NumPy and can’t wait to teach you all about it!

Topics we will cover:

We will cover a lot of different topics in this course. In order of appearance, they are:

  • Introduction to NumPy

  • Working with Vectors

  • Universal Functions and Plotting

  • Randomness and Statistics

  • Making and Modifying Matrices

  • Broadcasting and Advanced Indexing

  • Basic Linear Algebra

  • Understanding n-dimensional Arrays

  • Fourier Transforms

  • Advanced Linear Algebra

  • Saving and Loading Data

By completing our course, you will be comfortable with NumPy and have a solid foundation for topics like data science and machine learning in Python.

Still not decided?

The course has a 30-day refund policy, so if you are unhappy with the course, then you can get your money back painlessly. If are still uncertain after reading this, then take a look at some of the free previews and see if you enjoy them. Hope to see you soon!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to the Course

Lecture 2: Download all the Material

Lecture 3: Installing Anaconda

Lecture 4: Markdown Cells

Lecture 5: Code Cells

Lecture 6: Importing NumPy

Chapter 2: Working with Vectors

Lecture 1: Introduction

Lecture 2: Creating Vectors

Lecture 3: Basic Operations

Lecture 4: NumPy Datatypes

Lecture 5: Slicing Vectors

Lecture 6: Sorting Vectors

Lecture 7: Copies vs. Views

Lecture 8: Aggregate Funcitons

Lecture 9: Exercise Set – Temperature Data

Chapter 3: Universal Functions and Plotting

Lecture 1: Introduction

Lecture 2: Universal Functions

Lecture 3: Function Plot

Lecture 4: Bar and Scatter Plot

Lecture 5: Exercise Set – Temperature Data Continued

Chapter 4: Randomness and Statistics

Lecture 1: Introduction

Lecture 2: Generators and Random Integers

Lecture 3: Random, Shuffle, and Choice

Lecture 4: The Normal Distribution

Lecture 5: Basic Statistics

Lecture 6: Finding Unique Values

Lecture 7: Exercise Set – Linear Regression

Chapter 5: Making and Modifying Matrices

Lecture 1: Introduction

Lecture 2: Making and Modifying Matrices

Lecture 3: Attributes of a Matrix

Lecture 4: Changing the Shape of a Matrix

Lecture 5: Specifying an Axis

Lecture 6: Boolean Matrices

Lecture 7: Exercise Set – Rain Data

Chapter 6: Broadcasting and Advanced Indexing

Lecture 1: Introduction

Lecture 2: Basic Broadcasting

Lecture 3: Broadcasting Rules

Lecture 4: 2D Slicing

Lecture 5: Advanced Indexing

Lecture 6: Exercise Set – Monochromatic Images

Chapter 7: Basic Linear Algebra

Lecture 1: Introduction

Lecture 2: Basic Linear Algebra

Lecture 3: Cross Product and Length

Lecture 4: Matrix Operations

Lecture 5: Solving Linear Systems I

Lecture 6: Solving Linear Systems II

Lecture 7: Exercise Set – Basic Linear Algebra

Chapter 8: Understanding ndarrays

Lecture 1: Introduction

Lecture 2: Making Higher Dimensional Arrays

Lecture 3: Slicing and Aggregate Functions

Lecture 4: Colored Images

Lecture 5: What are Strides?

Lecture 6: Exercise Set – Color Images

Chapter 9: Fourier Transforms

Lecture 1: Introduction

Lecture 2: Complex Numbers

Lecture 3: Fourier Transforms I

Lecture 4: Fourier Transforms II

Lecture 5: Smoothing a Signal

Lecture 6: 2D Fourier Transforms

Lecture 7: Exercise Set – Fourier Transforms

Chapter 10: Advanced Linear Algebra

Lecture 1: Introduction

Lecture 2: Finding Eigenvalues and Eigenvectors

Lecture 3: Types of Matrices

Lecture 4: QR Decomposition

Lecture 5: Partial Least Squares

Lecture 6: Exercise Set – Quadratic Approximations & More

Chapter 11: Saving and Loading Data

Instructors

  • TM Quest
    TM Quest
    Technology and Mathematics Quest

Rating Distribution

  • 1 stars: 1 votes
  • 2 stars: 0 votes
  • 3 stars: 13 votes
  • 4 stars: 63 votes
  • 5 stars: 117 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!

You may also like

Top 10 Ethical AI Courses to Learn in November 2024

Top 10 Game Development Courses to Learn in November 2024

Top 10 Software Testing Courses to Learn in November 2024