NumPy - Module 4 Part 2

Welcome to Module 4 – Data Handling (Part 2)!
In this video, we introduce NumPy, one of the most powerful Python libraries used for scientific and numerical computing.

This class is explained in a simple, easy-to-understand manner—perfect for beginners and students following the KTU syllabus.

🔍 Topics Covered in This Class

✔ What is NumPy?
✔ Importance of NumPy in Data Science
✔ Creating ndarrays (1D, 2D, 3D)
✔ Array indexing & slicing (1D & 2D)
✔ Boolean indexing and fancy indexing
✔ Array arithmetic (addition, multiplication, scalar operations)
✔ Transpose of arrays
✔ Pseudorandom number generation
✔ Basic linear algebra using NumPy (dot product, determinant, inverse, eigenvalues)

After watching this class, you will understand:

👉 Why NumPy is faster than Python lists
👉 How to create and manipulate arrays
👉 How vectorized operations make coding easier
👉 How to perform mathematical operations efficiently
👉 Real-time use cases of NumPy in Machine Learning & Data Science

Perfect for:
📌 BCA / BSc CS / BTech / MTech Students
📌 KTU Syllabus – Module 4
📌 Python beginners
📌 Anyone learning data analysis or machine learning

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