Neural Networks from Scratch – No Prep Lesson Pack – Book 2 Unit 04

Neural Networks from Scratch – No Prep Lesson Pack – Book 2 Unit 04

A complete, classroom-ready neural networks teaching resource for intermediate Computer Science, ICT, STEM, artificial intelligence, machine learning, Python and data science lessons.

This no-prep lesson pack introduces students to the foundations of neural networks, from the basic idea of artificial neurons to layers, activation functions, forward passes, loss functions and backpropagation. Students also explore how the same core ideas connect to NumPy-based examples and beginner-friendly Keras workflows.

This resource is prepared as part of Fatih ARICA’s AI & Machine Learning Intermediate teaching resource series and is designed to support the AI & Machine Learning: European Edition learning sequence.

What is included:

• Course Promo Page PDF and editable DOCX
• Full Teacher Package PDF and editable DOCX
• Lesson Plan PDF and editable DOCX
• Summary Notes PDF and editable DOCX
• Student Worksheet PDF and editable DOCX
• Answer Key PDF and editable DOCX
• Teacher Handbook PDF and editable DOCX
• Printable Activity Cards PDF and editable DOCX
• Exit Tickets PDF and editable DOCX
• PowerPoint slide deck
• 800 × 600 TES cover image
• Read Me First file

Students will learn to:

• Explain what a neural network is in beginner-friendly language
• Connect artificial neurons with inputs, weights, bias and outputs
• Understand the role of layers in network architecture
• Compare activation functions such as sigmoid, ReLU and softmax
• Describe the forward pass as the process of making a prediction
• Understand loss functions as a way to measure model error
• Explain backpropagation as the process used to update weights
• Recognise how NumPy can be used to build simple neural network logic
• Connect neural network training with responsible AI, bias and reliability

Ideal for:

• Computer Science lessons
• ICT and digital skills lessons
• STEM enrichment
• Artificial intelligence and machine learning units
• Python machine learning lessons
• Data science introduction lessons
• Intermediate AI / ML teaching
• Secondary, high school and vocational education
• Non-specialist teachers introducing neural network concepts

Series information:

This is Book 2 Unit 04 of the AI & Machine Learning Intermediate Series.

Previous units:
Book 2 Unit 01 – Regression Algorithms
Book 2 Unit 02 – Unsupervised Learning & Clustering
Book 2 Unit 03 – Model Evaluation & Validation

Continue with:
Book 2 Unit 05 – Deep Learning with TensorFlow & Keras
Book 2 Unit 06 – Computer Vision
Book 2 Unit 07 – Natural Language Processing

This resource can be used as a standalone complete lesson pack or as part of the full intermediate AI and Machine Learning teaching sequence.

Resource details:

Resource type: Lesson (complete)
Age range: 14-16, 16+
Subject: Computer Science
Level: Intermediate AI & Machine Learning
Format: PDF, editable DOCX and PowerPoint PPTX files