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FREE AI RESOURCES

How can schools integrate artificial intelligence (AI) thanks to online tools and exciting resources?

Integrating Artificial Intelligence (AI) into schools requires a holistic approach that includes teachers, students, and school management. Here are some steps schools can take to successfully integrate AI:

CHECKLIST

Checkliste
Educate and train
teachers:

Start training courses for teachers to teach them the basics of open source AI.

Offer workshops to demonstrate the use of open source AI in different subjects.

Enable the exchange of best practices and experiences between teachers.

Development of teaching materials:

Create teaching materials that are specifically tailored to open source AI.

Integrate practical examples and projects to give students hands-on experience.

Enable the exchange of best practices and experiences between teachers.

Educate and train
teachers:

Start training courses for teachers to teach them the basics of open source AI.

Offer workshops to demonstrate the use of open source AI in different subjects.

Educate and train
teachers:

Start training courses for teachers to teach them the basics of open source AI.

Offer workshops to demonstrate the use of open source AI in different subjects.

Open Source für Schulen
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AI-supported tool for lesson development with over 100 resource types. Enables instant translation of generated content into more than 15 languages.

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AI-supported text-to-image generator to promote creativity in writing.

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AI-supported text-to-image generator to promote creativity in writing.

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AI-supported text-to-image generator to promote creativity in writing.

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AI-supported text-to-image generator to promote creativity in writing.

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AI-supported virtual tutor for individualised learning experiences.

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AI-supported virtual tutor for individualised learning experiences.

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AI-supported virtual tutor for individualised learning experiences.

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AI-supported virtual tutor for individualised learning experiences.

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A comprehensive platform for deep learning projects. Offers high-quality APIs such as Keras to simplify the modelling process.

TensorFlow:

Popular frameworks for deep learning.PyTorch uses a dynamic graph model, while Keras provides a high-level API for deep learning tasks.

Pytorch and Keras
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An open source framework for deep learning that supports various programming languages and is suitable for research purposes as well as for the productive implementation of machine learning models.

Apache MXNet:
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Popular open source library for Natural Language Processing (NLP).
Enables the simple and efficient use of transformation models such as GPT, BERT and RoBERTa.

Hugging Face Transformer
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A well-known library for computer vision and image processing developed by Intel, containing functions for image processing tasks such as feature recognition, object recognition and camera calibration.

OpenCV:
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Microsoft offers various resources and initiatives in the area of open source AI. These include the GitHub open source programme, Microsoft Open Source and the "Open at Microsoft" web series.

Microsoft Open Source Initiatives:

Popular frameworks for deep learning.PyTorch uses a dynamic graph model, while Keras provides a high-level API for deep learning tasks.

Pytorch and Keras
Externe Plattformen

Target group

Students, professionals

​Benefits

Free access, broad promotion of AI skills, fellowship program.

Content | Objectives

Promotion of AI skills, online courses on AI basics and specific topics.

KI macht Schule.de

Target group

Students and teachers

Advantages

Interactive educational offerings about AI, communicating challenges and opportunities.

Content | Goals

Workshops and courses on AI and machine learning.

KI macht Schule.de

Target group

Students and teachers

Advantages

Extensive resources, privacy-friendly tools, free to use.

Content | Goals

Workshops and courses on AI and machine learning.

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