NumPy Fundamentals for Data Analytics in Python

Master Core NumPy Skills for Real-World Data Analysis

What you'll learn
- Learn how to work with NumPy arrays
- Your 2nd step after the course "Base Python for Data Analytics" towards mastering Data Analytics
- Handle numerical data
- Data Analytics

Requirements
- Prior knowledge in Python programming is required
- The course "Base Python for Data Analytics" would be a perfect pre-requisite.

Description
Welcome! It is great to have you here. This hands-on course is your comprehensive guide to masteringNumPy, the foundational library for numerical computing in Python—essential for any data analyst, scientist, or backend engineer.

Whether you're preparing for a career in data analytics or strengthening your Python data skills, this course will walk you through NumPymethod-by-method, directly aligned with the official documentation. With a clear, structured approach, you'll gain a deep understanding of NumPy arrays, broadcasting, linear algebra, datetime operations, string handling, logic functions, masked arrays, statistical methods, and more.

Every concept is taught through focused, practical lectures. After each lesson, you'll reinforce your learning with:

A short3-question quizto test core understanding

A5-question hands-on exerciseprovided via Jupyter Notebook

The course wraps up with a set ofreal-world mini capstone projectsfrom domains like e-commerce, manufacturing, healthcare, and social media—designed to build job confidence and demonstrate how NumPy powers real data solutions.

By the end of the course, you’ll be able to use NumPy confidently in data analysis pipelines, troubleshoot issues efficiently, and recognize when and how to use specific NumPy functions for performance and clarity.

Prerequisite:A working knowledge of Python is required. This is not an introductory programming course.

Who this course is for:
- Beginners in data analytics who already know a bit of Python and would like to build a solid foundation in NumPy
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