Artificial Neural Network for Beginners

Artificial Neural Networks (ANNs) are at the core of modern Artificial Intelligence. This beginner-friendly course is designed to introduce you to the concepts, structures, and applications of ANNs without the need for any programming knowledge. Using intuitive explanations, real-world examples, and clear visualizations, you’ll learn how artificial neurons work, how networks are trained, and where they’re applied in today’s world.

By the end of this course, you’ll have a solid understanding of how neural networks function and the confidence to explore more advanced AI and deep learning topics.

What you’ll learn

• Understand the fundamentals of Artificial Neural Networks (ANNs).

• Learn how biological neurons inspire artificial networks.

• Explore key ANN architectures and learning mechanisms.

• Build intuition to move toward machine learning and AI topics.

Who this course is for:

• Beginners with no programming background.

• Students wanting to understand ANN concepts clearly.

• Non-technical learners interested in AI and machine learning.

• Professionals seeking AI knowledge without coding complexity.

Course Curriculum

Section 1: Introduction to Neural Networks

• Biological vs. Artificial Neurons

• Real-world applications

Section 2: Fundamentals of Artificial Neurons

• Structure of a neuron

• Activation functions

• Simple examples

Section 3: Architecture of Neural Networks

• Single-layer and multi-layer perceptron's

• Forward propagation

Section 4: Learning in Neural Networks

• Training and loss functions

• Gradient descent & backpropagation (conceptual)

Section 5: Types of Neural Networks

• Feedforward, CNNs, RNNs

• Other architectures overview