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 Duration 14 hours

Course Outline

Overview of Explainable Artificial Intelligence (XAI)

  • Definition and scope of Explainable AI (XAI)
  • The necessity of transparency in AI governance
  • Primary obstacles to AI model interpretability

Foundational XAI Methodologies

  • Model-agnostic approaches: LIME and SHAP
  • Model-specific interpretability techniques
  • Clarifying decisions generated by opaque (black-box) models

Practical Application of XAI Tools

  • Orientation to open-source XAI libraries for government use
  • Integrating XAI into foundational machine learning models
  • Visualization of model behavior and explanatory outputs

Obstacles in Achieving Explainability

  • Balancing model accuracy against interpretability
  • Constraints of existing XAI methodologies
  • Mitigating bias and ensuring fairness in explainable models

Ethical Frameworks for XAI

  • Analysis of ethical implications surrounding AI transparency
  • Equilibrium between explainability and operational performance
  • Privacy and data safeguarding issues within XAI

Application of XAI in Public Sector and Critical Sectors

  • XAI implementation in healthcare, financial regulation, and law enforcement
  • Compliance with regulatory standards for explainability
  • Fostering public trust in AI systems via transparency

Advanced XAI Theoretical Concepts

  • Investigation of counterfactual explanations
  • Interpretation of neural networks and deep learning architectures
  • Analysis of complex AI system behaviors

Prospective Developments in Explainable AI

  • Emerging research techniques in XAI
  • Future challenges and opportunities for AI transparency
  • Influence of XAI on the development of responsible AI for government

Conclusions and Implementation Roadmap

Requirements

  • Foundational knowledge of machine learning principles
  • Proficiency in Python programming

Intended Audience

  • Professionals new to AI applications
  • Data science practitioners and enthusiasts

Number of participants


Price per participant

Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.

Upcoming Courses

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