Numpy Library | Python for Blind - L17 | Programming with NVDA

📌 Learn NumPy for Beginners with NVDA Screen Reader Support | Python for Visually Impaired Welcome to this beginner-friendly tutorial on the NumPy library in Python, designed to be fully accessible using the NVDA screen reader. Whether you're just starting out or want to strengthen your fundamentals, this video provides a clear and hands-on introduction to NumPy with real-time code demonstrations. You can check the time stamps right here: 00:00 Introduction 1:42 Applications of NumPy 5:55 installation & importing of numpy 9:25 Creating arrays 10:30 Common properties of arrays 15: 10 2D Arrays 16:10 Visualization of 2D Arrays 19:08 Indexing 21:50 Datatypes 28:00 Difference between list & arrays 30:30 Common aggregate functions 32:00 Axes in Arrays 38:25 3D Array Explanation 41:52 Indexing & Slicing in 2D arrays 48:10 Matrix operations 51:55 Concatenate 2 matrices 55:50 Arange & linspace 01:01:25 Vectorization 🔍 Topics Covered: ✅ What is NumPy and Why is it Used ✅ Applications of NumPy:  • Numerical Computation  • Arrays & Matrices  • Scientific Computing ✅ Creating Arrays:  • 1D & 2D Arrays  • Slicing Sub-Arrays ✅ Indexing & Slicing Techniques ✅ Understanding Array Properties:  • .shape, , .dtype, .ndim ✅ Aggregate Functions:  • sum, prod, sqrt, log and more ✅ Matrix Operations:  • Element-wise Multiplication  • Matrix Multiplication  • Inverse of a Matrix using numpy.linalg ✅ Working with Axes in NumPy ✅ Axis-wise Operations (axis=0, axis=1 explained) 🎧 Specially designed for screen reader users, with clear audio, structured explanations, and keyboard-only navigation using NVDA. 💡 Whether you're learning for data science, AI/ML, or general-purpose coding — this tutorial lays a strong foundation for using NumPy efficiently and accessibly. 🔔 Subscribe for more accessible Python and data science tutorials! 📢 Comment below if you need the code or want follow-up videos on advanced topics! #sightlesssystems #numpy #Python #Accessibility #ScreenReader #NVDA #BlindProgrammers #DataScience #PythonTutorials #InclusiveCoding #BeginnerFriendly #AIForAll