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The Complete Python NumPy Tutorial

Discover the power of NumPy with our comprehensive Python NumPy tutorial. Ideal for beginners in data science. Start now! Read more.

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Course Skill Level
Beginner
Time Estimate
3h 16m

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About This Course

Who this course is for:

  • Beginners with basic Python knowledge looking to get started with NumPy
  • Learners who want to develop practical NumPy skills through 70+ hands-on exercises
  • Individuals seeking a solid foundation in NumPy for data science applications

What you’ll learn:

  • Foundational NumPy concepts for numerical and scientific computing
  • Efficient array manipulation techniques using slicing, joining, splitting, reshaping, indexing, and searching
  • Best practices for effective NumPy programming

Requirements:

  • Computer with Internet access
  • Basic understanding of Python

Welcome to The Complete Python NumPy Tutorial by Studyopedia!

Mastering the Fundamentals of NumPy

NumPy, short for Numerical Python, is a powerful open-source library that empowers you to work with multi-dimensional arrays and matrices in Python. 

Written in both Python and C for performance, it provides efficient tools for numerical computations with less code. NumPy is a foundational library in data science because it can manage complex data structures and execute advanced mathematical operations.

Our Python NumPy tutorial covers all key operations, including:

  • Array Slicing: Extract specific portions of an array
  • Array Joining: Combine multiple arrays into a single unit
  • Array Splitting: Divide an array into smaller sub-arrays
  • Array Reshaping: Change the dimensionality (shape) of an array
  • Array Indexing: Access individual elements or subsets of an array
  • Array Searching: Locate specific values within an array

Future-proof your career! My courses provide the skills needed to stay relevant in a changing job market. Click here!

Our Promise to You

By the end of this course, you will have learned how to effectively use NumPy to handle complex data structures, perform advanced mathematical operations, and apply best practices for numeric and scientific computing in Python.

10 Day Money Back Guarantee. If you are unsatisfied for any reason, simply contact us and we’ll give you a full refund. No questions asked.

Get started today!

Course Curriculum

Section 1 - NumPy - Introduction And Setup
NumPy Introduction And Features 00:00:00
Install NumPy (Set Environment) 00:00:00
Section 2 - NumPy - Basics
Create NumPy Arrays 00:00:00
Dimensions In NumPy Arrays 00:00:00
Initialize NumPy Arrays 00:00:00
NumPy DataTypes 00:00:00
Section 3 - NumPy - Indexing and Slicing
NumPy Array Indexing 00:00:00
NumPy Array Slicing 00:00:00
Section 4 - NumPy - Shape, Reshape, Iterate
Array Shape 00:00:00
Reshape A NumPy Array 00:00:00
Iterate A NumPy Array 00:00:00
Section 5 - NumPy - Join, Split, Search, Sort
Join NumPy Arrays 00:00:00
Split NumPy Arrays 00:00:00
Search A NumPy Array For A value 00:00:00
Sort NumPy Arrays 00:00:00
Axes In NumPy Arrays 00:00:00
Section 6 - NumPy - Operations
Intersection Of NumPy Arrays 00:00:00
Difference Between NumPy Arrays 00:00:00
Arithmetic Operations On NumPy Arrays 00:00:00
Scalar Operations On NumPy Arrays 00:00:00
Statistical Operations On NumPy Arrays 00:00:00
Section 7 - NumPy - Miscellaneous
Random Module In NumPy 00:00:00
NumPy Logs 00:00:00
NumPy LCM And HCF 00:00:00

About This Course

Who this course is for:

  • Beginners with basic Python knowledge looking to get started with NumPy
  • Learners who want to develop practical NumPy skills through 70+ hands-on exercises
  • Individuals seeking a solid foundation in NumPy for data science applications

What you’ll learn:

  • Foundational NumPy concepts for numerical and scientific computing
  • Efficient array manipulation techniques using slicing, joining, splitting, reshaping, indexing, and searching
  • Best practices for effective NumPy programming

Requirements:

  • Computer with Internet access
  • Basic understanding of Python

Welcome to The Complete Python NumPy Tutorial by Studyopedia!

Mastering the Fundamentals of NumPy

NumPy, short for Numerical Python, is a powerful open-source library that empowers you to work with multi-dimensional arrays and matrices in Python. 

Written in both Python and C for performance, it provides efficient tools for numerical computations with less code. NumPy is a foundational library in data science because it can manage complex data structures and execute advanced mathematical operations.

Our Python NumPy tutorial covers all key operations, including:

  • Array Slicing: Extract specific portions of an array
  • Array Joining: Combine multiple arrays into a single unit
  • Array Splitting: Divide an array into smaller sub-arrays
  • Array Reshaping: Change the dimensionality (shape) of an array
  • Array Indexing: Access individual elements or subsets of an array
  • Array Searching: Locate specific values within an array

Future-proof your career! My courses provide the skills needed to stay relevant in a changing job market. Click here!

Our Promise to You

By the end of this course, you will have learned how to effectively use NumPy to handle complex data structures, perform advanced mathematical operations, and apply best practices for numeric and scientific computing in Python.

10 Day Money Back Guarantee. If you are unsatisfied for any reason, simply contact us and we’ll give you a full refund. No questions asked.

Get started today!

Course Curriculum

Section 1 - NumPy - Introduction And Setup
NumPy Introduction And Features 00:00:00
Install NumPy (Set Environment) 00:00:00
Section 2 - NumPy - Basics
Create NumPy Arrays 00:00:00
Dimensions In NumPy Arrays 00:00:00
Initialize NumPy Arrays 00:00:00
NumPy DataTypes 00:00:00
Section 3 - NumPy - Indexing and Slicing
NumPy Array Indexing 00:00:00
NumPy Array Slicing 00:00:00
Section 4 - NumPy - Shape, Reshape, Iterate
Array Shape 00:00:00
Reshape A NumPy Array 00:00:00
Iterate A NumPy Array 00:00:00
Section 5 - NumPy - Join, Split, Search, Sort
Join NumPy Arrays 00:00:00
Split NumPy Arrays 00:00:00
Search A NumPy Array For A value 00:00:00
Sort NumPy Arrays 00:00:00
Axes In NumPy Arrays 00:00:00
Section 6 - NumPy - Operations
Intersection Of NumPy Arrays 00:00:00
Difference Between NumPy Arrays 00:00:00
Arithmetic Operations On NumPy Arrays 00:00:00
Scalar Operations On NumPy Arrays 00:00:00
Statistical Operations On NumPy Arrays 00:00:00
Section 7 - NumPy - Miscellaneous
Random Module In NumPy 00:00:00
NumPy Logs 00:00:00
NumPy LCM And HCF 00:00:00
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