Understanding AI from Scratch – Neural Networks Course” is designed for beginners who want a clear and practical introduction to artificial intelligence and deep learning. The course starts with the basics of AI, explaining machine learning, supervised and unsupervised learning, and their applications. Learners then explore neural networks, understanding how neurons, layers, and activation functions work together to model complex data. Key concepts such as forward propagation, backpropagation, and gradient descent are explained intuitively, helping students grasp how networks learn from data. Practical exercises and examples enable learners to build and train simple neural networks using Python, applying AI techniques to real-world problems like image recognition and predictive modeling. By the end of the course, participants will have a strong foundational understanding of AI principles and neural network architectures, empowering them to advance into more specialized AI and deep learning topics. This course is ideal for coders, data enthusiasts, and anyone seeking to start a career in artificial intelligence