Neural Networks Fundamentals: Build a Handwriting Classifier

Artificial intelligence is transforming modern technology, but understanding how neural networks actually function does not have to be overwhelming. This course guides you through deep learning principles from the ground up, helping you understand how artificial neurons process data and discover complex patterns. You will gain the core knowledge required to design, train, and evaluate a neural network capable of recognizing handwritten numbers. What you will learn: Learn essential machine learning terminology and foundational mathematical concepts. Understand how artificial neurons, hidden layers, and activation functions pass information. Implement forward propagation and backpropagation algorithms through practical code snippets. Train and optimize neural network parameters using gradient descent and loss functions. Explore modern deep learning practices, framework conventions, and evaluation metrics. The course begins with clear definitions and core architectural ideas before moving into multi-layer networks and practical code implementations. Designed for beginner developers, tech enthusiasts, and curious learners with basic programming literacy who want to enter the field of machine learning. Start reading today to unlock the fundamentals of artificial intelligence.