Course Outline

Introduction to Artificial Intelligence (AI), Machine Learning (ML) and Data Science for Government

  • Historical context of AI and its integration with combinatorial technologies
  • Overview of AI, including concepts, narrow, and general AI
  • The AI process: sense, reason, act
  • Cognitive processes in AI: machine learning
  • Advanced analytics compared to artificial intelligence
  • Past, present, and future perspectives on AI
  • Four types of data analytics
  • The value chain in analytics
  • Algorithms explained without technical jargon
  • Supervised learning methods
  • Unsupervised learning techniques
  • Reinforcement learning strategies
  • Data as a critical resource for AI
  • Structured and unstructured data, including the 5 V's of data
  • Principles of data governance
  • The data engineering platform in government contexts
  • Essential concepts for understanding data architecture
  • Big data reference architecture for government
  • Three categories of data usage in public sector applications

AI Opportunity Matrix

Successful Use Cases by Porter's Value Chain

  • Primary activities enhanced by AI
  • Supporting activities optimized through AI

Successful Use Cases by Technology

  • Natural Language Processing (NLP)
  • Image recognition technologies
  • Machine learning applications

Ideation of AI Projects for Government

  • The AI Funnel process for project ideation
  • Various approaches to idea generation
  • Prioritizing AI projects based on impact and feasibility
  • The AI project canvas for structured planning

Running AI Projects for Government

  • The machine learning life cycle in government projects
  • The AI machine learning canvas for project management
  • Decision-making framework: when to develop and when to procure AI solutions

Transforming into an AI-Ready Organization for Government

  • Utilizing the AI strategy cycle for organizational transformation
  • Dimensions of the AI framework for government operations
  • Practical approaches to assess AI maturity in public sector organizations
  • Optimal organizational structures for AI integration
  • Benefits of establishing an AI Center of Excellence for government
  • Required skills and competencies for AI professionals in government

AI and Ethics for Government

  • Risks associated with AI in public sector applications
  • Ethical guidelines for responsible AI use
  • Strategies for achieving trustworthy AI in government
 35 Hours

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