NumPy for Scientific Computation with Python – 2022 Edition
NumPy for Scientific Computation with Python – 2022 Edition, available at $19.99, has an average rating of 4.1, with 7 lectures, based on 13 reviews, and has 1636 subscribers.
You will learn about Learn what is NumPy, its history and benefits. Learn to install and import NumPy in Python. Learn the basics of NumPy arrays. Learn the different ways to create NumPy arrays. Learn how to perform indexing and slicing on NumPy arrays. Learn how to perform various NumPy operations. Learn how to save and load NumPy arrays in different file formats. This course is ideal for individuals who are Beginner Python developers curious about data science or Mathematicians looking to work with multi-dimensional arrays It is particularly useful for Beginner Python developers curious about data science or Mathematicians looking to work with multi-dimensional arrays.
Enroll now: NumPy for Scientific Computation with Python – 2022 Edition
Summary
Title: NumPy for Scientific Computation with Python – 2022 Edition
Price: $19.99
Average Rating: 4.1
Number of Lectures: 7
Number of Published Lectures: 7
Number of Curriculum Items: 7
Number of Published Curriculum Objects: 7
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn what is NumPy, its history and benefits.
- Learn to install and import NumPy in Python.
- Learn the basics of NumPy arrays.
- Learn the different ways to create NumPy arrays.
- Learn how to perform indexing and slicing on NumPy arrays.
- Learn how to perform various NumPy operations.
- Learn how to save and load NumPy arrays in different file formats.
Who Should Attend
- Beginner Python developers curious about data science
- Mathematicians looking to work with multi-dimensional arrays
Target Audiences
- Beginner Python developers curious about data science
- Mathematicians looking to work with multi-dimensional arrays
Are you a beginner looking to kick off your career in data science using Python? Then, this course on NumPy is a must for you!
NumPy, or Numerical Python, is an open-source Python library that helps you perform simple as well as complex computations on numerical data. It is the go-to scientific computation library for beginners as well as advanced Python programmers and it is used mostly by statisticians, data scientists, and engineers.
In this course, you will learn everything you need to know about NumPy arrays starting from how to install NumPy and import it in Python. You will be introduced to various methods of creating NumPy arrays and you will also learn various operations on them. Furthermore, the course helps you learn how to perform indexing and slicing on NumPy arrays. The course ends off by teaching you how to save/load NumPy arrays in different file formats.
Why you should take this course?
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Updated 2022 course content: All our course content is updated as per the latest technologies and tools available in the market
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Practical hands-on knowledge: This course is oriented to providing a step-by-step implementation guide rather than just sticking to the theory.
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Guided support: We are always there to guide you through the Q/As so feel free to ask us your queries.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Welcome to the course!
Lecture 2: Introduction to NumPy
Lecture 3: Basics of NumPy Array
Lecture 4: Creating NumPy Arrays
Lecture 5: NumPy Array Indexing and Slicing
Lecture 6: Input/Output Operations in NumPy
Lecture 7: Bonus Lecture
Instructors
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The Click Reader
Teaching Data Science and Machine Learning
Rating Distribution
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- 3 stars: 3 votes
- 4 stars: 4 votes
- 5 stars: 6 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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