Data Visualisation with Matplotlib & Seaborn – No Prep Lesson Pack – Unit 04

AI & Machine Learning Fundamentals – Complete No Prep Teaching Bundle – Units 01–07

A complete, classroom-ready Artificial Intelligence and Machine Learning teaching bundle for beginner Computer Science, ICT, STEM, digital literacy, Python, data science and vocational education lessons. This bundle includes 7 complete no-prep lesson packs designed to introduce students to artificial intelligence, machine learning, data handling, data visualisation, Scikit-learn and classification algorithms in a clear, structured and teacher-friendly way. Each unit is designed for teachers who want ready-to-use lesson materials without building slides, worksheets, answer keys and activities from scratch. No advanced AI or machine learning experience is required. Units included 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: Workflow, Training & Evaluation Unit 06 – Scikit-learn in Depth Unit 07 – Classification Algorithms What is included in each unit Each unit includes: Full Teacher Pack PDF and editable DOCX Lesson Plan PDF and DOCX Student Worksheet PDF and editable DOCX Answer Key PDF and DOCX Summary Notes PDF and DOCX Printable Activity Cards PDF and DOCX Exit Tickets PDF and DOCX Teacher Handbook PDF and DOCX PowerPoint slide deck 800 × 600 TES cover image Read Me First file Students will learn to Understand what artificial intelligence is and how it is used in real life Explain key AI and machine learning concepts in beginner-friendly language Set up and choose appropriate AI development tools such as Python, Jupyter, Google Colab, Kaggle and VS Code Work with data using NumPy and Pandas Interpret data using Matplotlib and Seaborn visualisations Understand the machine learning workflow, including training, testing and evaluation Use Scikit-learn concepts such as estimators, pipelines, cross-validation and GridSearchCV Compare classification algorithms including K-Nearest Neighbours, Decision Trees, Support Vector Machines and Random Forests Discuss responsible AI, bias, fairness, transparency and real-world AI risks Ideal for Computer Science lessons ICT and digital skills lessons STEM enrichment Artificial intelligence and machine learning units Beginner Python and data science lessons Secondary school and high school teaching Vocational education Non-specialist teachers introducing AI and machine learning Why this bundle is useful This bundle gives teachers a complete beginner-friendly AI and machine learning teaching sequence. The resources can be used as individual standalone lessons or taught as a connected unit across several weeks. The materials are designed to be practical, structured and classroom-ready, with teacher guidance, student worksheets, printable activities, exit tickets, answer keys and editable files included throughout. Resource details Resource type: Lesson bundle / Unit of work Age range: 14-16, 16+ Subject: Computer Science Language: English Format: PDF, editable DOCX and PowerPoint PPTX files