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  1. Edx Education My Gears Machine Set - Educational Construction Toy - Multicolor

  2. ABS Kid Children Tablet Pad Learning Letters Words Numbers Educational

    High‑quality children's learning tablet, sturdy and durable, carefully designed to withstand the daily use of your child during growth. The content of learning and playing, simple function, no LED harm to children's eyes, is a good choice of toys for babies.

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  3. BBC Microbit V2.2 Starter Kit, Micro Bit Car Kit, Electronic Programming Kit for

    Personal computer design type : Barebone. Specific uses for product : Education, Robotics.

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  4. AQA Computer Science for GCSE Student Book (Aqa Gcse) By Steve Cushing

    Title: AQA Computer Science for GCSE Student Book (Aqa Gcse) Item Condition: used item in a very good condition. Author: Steve Cushing ISBN 10: 147186619X. Used-like N : The book pretty much look like a new book.

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  5. 4GB RAM, 128GB Storage, WiFi, Blue Kids 10.1 Inch Education Android Tablet

    ⚙️ Android 12 with Quad-Core Processor. Perfect for travel, school, or play — kids can enjoy uninterrupted fun without frequent charging. Great for virtual learning, family chats, or creative photography.

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  6. Pearson REVISE Edexcel GCSE Computer Science Revision Guide incl. online revisi

    Online revision - for 2026, 2027 exams. We have a support team to assist you.

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  7. Vintage Number Chaser Educational Game Software Cassette For Commodore Plus/4

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  8. Android Phones for Seniors in easy steps, 4th edition

    Th edition unravels the world of Android smartphones. It provides an overview of the popular models, and then shows how to Introducing Android Phones. Android Settings. Around an Android Phone. Command your phone to search for anything on your phone or on the web, using the keyboard or the voice assistant.

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  9. Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and...

    Courses and books on basic statistics rarely cover the topic from a data science perspective. Why exploratory data analysis is a key preliminary step in data science. How random sampling can reduce bias and yield a higher-quality dataset, even with big data.

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