Boost Your Data Science Skills with Numpy Coding Exercises

Welcome to the comprehensive guide to mastering Numerical Python, also known as Numpy. In this course, we dive deep into the Numpy library within the Python Programming Language, offering real-time coding exercises in Jupyter Notebook. Our aim is to demystify Numpy’s functionality and empower you with the ability to leverage its power for efficient numerical computations. Numpy arrays are the cornerstone of numerical computing in Python. They provide a high-performance alternative to Python’s built-in lists and tuples, enabling lightning-fast mathematical operations. Throughout this course, you’ll explore a plethora of Numpy commands, equipping you with the skills to tackle a wide range of numerical tasks effortlessly. Let’s embark on this journey to unlock the full potential of Numpy and revolutionize your approach to numerical computations. Whether you’re a beginner or an experienced Python programmer, this course offers valuable insights and practical exercises to elevate your proficiency in numerical computing.

What you will learn:

• Understand the fundamentals of the Python Numpy library
• Numpy Arrays – 1D, 2D, 3D, Zeros, Ones, Full Arrays etc
• Numpy Functions – Random, Linspace, Empty, Eye, Identity, Transpose, Diagonal Function etc
• Indexing in Numpy Arrays
• You can download each lecture video and source codes files

Course Content:

• Sections: 1
• Lectures: 16
• Duration: 2h 34m

Requirements:

• Basic Python Programming knowledge
• You can use any one of these – Jupyter Notebook or PyCharm or Google Colab etc.

Who is it for?

• Data Science Beginners who are interested in Python.

What are you waiting for to get started?

Enroll today and take your skills to the next level. Coupons are limited and may expire at any time!

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