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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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  • Calendar

Trustworthy AI

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

Recorded lectures

Click https://drive.google.com/drive/folders/1AgZ5B95qMbNjveGeu7WsW8HaR3Jtorp5?usp=share_link link to open resource.
◄ Trustworthy AI™ - Bridging the ethics gap surrounding AI
Syllabus and Session Outlines ►
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TAI
Data retention summary