Scikit-learn in Depth – No Prep Lesson Pack – Unit 06

Scikit-learn in Depth – No Prep Lesson Pack – Unit 06

A complete, classroom-ready Scikit-learn teaching resource for beginner Computer Science, ICT, STEM, Python, artificial intelligence, machine learning and data science lessons.

This no-prep lesson pack introduces students to Scikit-learn as one of the most widely used Python libraries for machine learning. Students explore the basic Scikit-learn workflow, including datasets, features, labels, model training, prediction, evaluation and simple pipelines.

The unit helps students understand how machine learning models are built in practice using a clear, beginner-friendly structure. It introduces key ideas such as fit, predict, train/test split, preprocessing, model evaluation and responsible use of machine learning tools.

This resource is prepared as part of Fatih ARICA’s AI & Machine Learning Fundamentals 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
• Slide deck PDF
• 800 × 600 TES cover image
• Read Me First file
• TES product description file

Students will learn to:

• Explain what Scikit-learn is used for
• Understand features, labels, datasets and models
• Describe the basic fit and predict workflow
• Use train/test split to check model performance
• Recognise why preprocessing is important
• Understand simple machine learning pipelines
• Interpret basic evaluation results
• Connect Scikit-learn workflows with responsible AI, fairness and testing

Ideal for:

• Computer Science lessons
• ICT and digital skills lessons
• STEM enrichment
• Beginner Python lessons
• Artificial intelligence and machine learning units
• Data science introduction lessons
• Secondary, high school and vocational education
• Non-specialist teachers introducing practical machine learning

Series information:

This is Unit 06 of the AI & Machine Learning Fundamentals Series.

Previous units:
Unit 01 – Introduction to Artificial Intelligence
Unit 02 – AI Development Environment Setup
Unit 03 – Data Handling with NumPy & Pandas
Unit 04 – Data Visualisation with Matplotlib & Seaborn
Unit 05 – Machine Learning Basics

Continue with:
Unit 07 – Classification Algorithms

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

Resource details:

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