Computer Science & AI
Klassenstufen: Grade 2
Bildungssystem: STEM
Welcome to "AI Explorers" – a beginner-friendly, exciting journey into the world of Artificial Intelligence (AI) and Machine Learning (ML) designed especially for curious young minds in Grade 2! In this course, students will dive into the amazing world of AI using PictoBlox, a child-friendly, block-based programming platform. Through colorful blocks and interactive projects, kids will explore key AI concepts like image recognition, voice interaction, and smart decision-making — all in a playful, visual, and hands-on way. They’ll learn how computers can see, hear, and even think, just like humans. From training a computer to recognize different emotions to building their own smart assistant, students will develop logical thinking, creativity, and 21st-century tech skills while having tons of fun! No previous experience with programming or AI is required — just imagination and a willingness to explore! What Kids Will Learn: What is AI and how it works (in simple language) Introduction to Machine Learning Using PictoBlox to build AI projects Train computers to recognize faces, objects, and sounds Create smart, interactive games and stories Develop logical thinking, problem-solving, and creativity Tools Used: PictoBlox (block-based coding interface) Laptop/Tablet with internet connection Webcam and microphone (for AI features like image and voice detection)
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1. Define and explain core Artificial Intelligence (AI) and Machine Learning (ML) concepts.
Lernziele:
1. List and describe key AI terms such as data, algorithm, model, training, and prediction.
2. Differentiate between AI and ML using clear, simple examples.
3. Explain fundamental workings of AI models and decision-making processes in measurable terms.
4. Demonstrate understanding of technical vocabulary with precise definitions and examples.
Module
1. Discovering AI Fundamentals
1. 1. Introduction to Artificial Intelligence
Lernergebnisse:
1. Define artificial intelligence using precise and measurable terminology.
2. Identify major components of AI systems including data, algorithms, and hardware.
3. Explain the significance of AI in modern technology through observable examples.
4. Differentiate between rule-based and learning-based AI approaches using clear comparisons.
1. 2. History and Evolution of AI
Lernergebnisse:
1. Chronicle key milestones in AI development with specific dates and events.
2. Analyze paradigm shifts in AI history using measurable case studies.
3. Compare early AI models with contemporary applications using observable criteria.
4. Evaluate the impact of historical developments on current AI trends.
1. 3. Exploring Machine Learning Basics
Lernergebnisse:
1. Define machine learning and explain its relationship with AI using clear examples.
2. Illustrate supervised, unsupervised, and reinforcement learning using measurable distinctions.
3. Demonstrate training and testing phases through block-based simulations.
4. Identify differences between machine learning and traditional programming with observable comparisons.