Machine Learning Foundations Lesson Bundle | Grade 12 Computer Science | General — bundle cover
Machine Learning Foundations Lesson Bundle | Grade 12 Computer Science | General — included worksheet 1
Machine Learning Foundations Lesson Bundle | Grade 12 Computer Science | General — included worksheet 2
Machine Learning Foundations Lesson Bundle | Grade 12 Computer Science | General — included worksheet 3
Machine Learning Foundations Lesson Bundle | Grade 12 Computer Science | General — included worksheet 4
Machine Learning Foundations Lesson Bundle | Grade 12 Computer Science | General — included worksheet 5
Machine Learning Foundations Lesson Bundle | Grade 12 Computer Science | General — included worksheet 6
Grade 12 Computer Science worksheet — Machine Learning Foundations Lesson Bundle | Grade 12 Computer Science | General

Description

Overview


Machine Learning Foundations supports Grade 12 Computer Science in the General framework with 6 worksheets that build understanding of AI ethics, model evaluation, and core machine learning workflows. Students move from data representations (features and labels) to predictive modeling, then connect those ideas to neural networks and modern generative AI. This unit bundle is designed for classroom-ready instruction, with each worksheet targeting a distinct concept and practice task.

What's Included


  • ✅ AI Ethics and Model Evaluation Worksheet | Grade 12 Computer Science – Examine fairness, bias, and evaluation criteria while interpreting model performance signals.
  • ✅ Generative AI and Large Language Models Worksheet | Grade 12 Computer Science – Analyze how large language models generate outputs and what “quality” means in context.
  • ✅ Neural Networks and Deep Learning Worksheet | Grade 12 Computer Science – Connect layered representations to learning and describe how deep models improve with data and training.
  • ✅ Regression and Prediction from Data to Numbers Worksheet | Grade 12 CS – Use regression ideas to turn data into predictions, focusing on variables and interpretation.
  • ✅ Features and Labels Worksheet | Grade 12 Computer Science Machine Learning – Practice creating features and identifying labels for supervised learning tasks.
  • ✅ Machine Learning Foundations Data Features and Labels Worksheet | Grade 12 – Strengthen foundational understanding by classifying data into inputs (features) and targets (labels) for model-ready datasets.

Skills & Standards


Aligned to the General framework, these worksheets emphasize crosscutting skills such as modeling, analytical reasoning, and evidence-based explanations. Students learn to represent problems with data, describe relationships between inputs and outputs, and justify how evaluation measures relate to real-world decisions. Across the bundle, students practice core disciplinary ideas in computer science and AI: algorithmic systems learn patterns from examples, models can be assessed with appropriate metrics, and the context of deployment shapes what counts as “success.” Learners also build habits of scientific argumentation by interpreting results, recognizing limitations, and explaining conclusions using classroom evidence from each worksheet task.

Perfect For


  • Teachers seeking structured instruction
  • Sub plans
  • Homework or review
  • Intervention or centers
  • Assessment preparation

How to Use


Plan for 1–3 weeks of multi-day pacing, using 1 worksheet every 2–3 class periods depending on your schedule and student needs. Start with a short warm-up that previews vocabulary (features, labels, evaluation, prediction). Use guided practice to model how to translate a scenario into a dataset, then complete the worksheet independently with teacher check-ins. Close each session with an exit ticket that requires a brief, evidence-based explanation (for example, which metric best supports a claim about model performance) and use an end-of-unit review to compare predictions, evaluation ideas, and ethical considerations across tasks.

Closing


Machine Learning Foundations helps students connect data, modeling, and responsible AI thinking into a cohesive Grade 12 Computer Science experience.

Machine Learning Foundations Lesson Bundle | Grade 12 Computer Science | General

$24.00$30.00Save $6.00
Prism Point Learning
·2 followers·13 sales
SubjectComputer ScienceGradeGrade 12Pages183 Pages

What’s included

6 worksheets · 183 pages · Save $6.00 (20%) · prices shown inside the bundle

  1. Regression and Prediction from Data to Numbers Worksheet | Grade 12 CS
    Regression and Prediction from Data to Numbers Worksheet | Grade 12 CS

    Grade 12 · Computer Science · 31 Pages

    • Explain how regression models predict numerical outcomes and compare them to classification models
    • Identify factors that affect prediction accuracy, such as model fit and variable relationships
    • Choose the correct modeling approach for a given prediction problem and justify the choice
    $4.00$5.00
  2. Generative AI and Large Language Models Worksheet | Grade 12 Computer Science
    Generative AI and Large Language Models Worksheet | Grade 12 Computer Science

    Grade 12 · Computer Science · 30 Pages

    • Explain how large language models generate responses using patterns learned from large data sets.
    • Evaluate when generative AI is reliable and when human review is still necessary.
    • Identify common risks such as hallucinations, bias, and unsafe or incorrect outputs.
    $4.00$5.00
  3. Machine Learning Foundations Data Features and Labels Worksheet | Grade 12
    Machine Learning Foundations Data Features and Labels Worksheet | Grade 12

    Grade 12 · Computer Science · 31 Pages

    • Explain how training data, features, and labels affect a machine learning model’s predictions.
    • Identify common reasons data quality issues can reduce model performance.
    • Distinguish between features and labels and describe how training helps a model learn patterns.
    $4.00$5.00
  4. Neural Networks and Deep Learning Worksheet | Grade 12 Computer Science
    Neural Networks and Deep Learning Worksheet | Grade 12 Computer Science

    Grade 12 · Computer Science · 30 Pages

    • Explain how neural networks use layers of connected units to transform inputs into outputs.
    • Describe the role of weights in learning and how deep learning increases modeling capacity with more layers.
    • Interpret common neural network ideas such as inputs, layers, activation, and training objectives.
    $4.00$5.00
  5. AI Ethics and Model Evaluation Worksheet | Grade 12 Computer Science
    AI Ethics and Model Evaluation Worksheet | Grade 12 Computer Science

    Grade 12 · Computer Science · 31 Pages

    • Explain key AI ethics concepts: fairness, transparency, privacy, and accountability.
    • Apply model evaluation ideas to decide whether an AI system is trustworthy across different groups and situations.
    • Identify common sources of bias and unintended harmful outputs, and propose responsible evaluation steps.
    $4.00$5.00
  6. Features and Labels Worksheet | Grade 12 Computer Science Machine Learning
    Features and Labels Worksheet | Grade 12 Computer Science Machine Learning

    Grade 12 · Computer Science · 30 Pages

    • Explain how labels communicate meaning in user interfaces and data representations.
    • Identify common features of labeled interfaces, including readability, consistency, and clarity.
    • Evaluate statements about labels and their role in usability and data understanding.
    $4.00$5.00

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Who is Machine Learning Foundations Lesson Bundle | Grade 12 Computer Science | General designed for?
Machine Learning Foundations Lesson Bundle | Grade 12 Computer Science | General is designed for Grade 12 students and Computer Science learners and can be used in classrooms, homeschool, or independent practice.
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