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xAIM
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  • TAI
  • General
  • TAI Assignment
  • Establishing the rules for building trustworthy AI
  • THEORETICAL PART
  • PRACTICAL PART - Introduction to Statistical Learning models (Rec)
  • PRACTICAL PART - Model Selection (Rec)
  • PRACTICAL PART - Introduction to Machine Learning Models (Rec)
  • PRACTICAL PART - Python Practice 1 (Statistical and Machine Learning Models - Model Selection) (Rec)
  • PRACTICAL PART - Explainability of Artificial Intelligence methods (LIVE)
  • PRACTICAL PART - Reading Scientific Paper 1
  • PRACTICAL PART - Accuracy of Artificial Intelligence methods (Rec)
  • PRACTICAL PART - Python Practice 2 (Explainability and Accuracy of AI) (LIVE)
  • PRACTICAL PART - Reading Scientific Paper 2
  • PRACTICAL PART - S.A.F.E. Artificial Intelligence (Rec)
  • Realizing Trustworthy AI solutions for diagnosis and prognosis support
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Trustworthy AI

  1. Home
  2. Courses
  3. Ethical and Legal Considerations
  4. TAI
  5. THEORETICAL PART
  6. Data Management

Data Management

    • 1_NHSX_AI_report.pdf1_NHSX_AI_report.pdf
    • 8_Developing, implementing and governing artificial intelligence in medicine a step-by-step approach to prevent an artificial intelligence winter.pdf8_Developing, implementing and governing artificial intelligence in medicine a step-by-step approach to prevent an artificial intelligence winter.pdf
    • Data Management.pdfData Management.pdf
◄ Trustworthy AI Framework
Trustworthy AI™ - Bridging the ethics gap surrounding AI ►
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TAI
Data retention summary