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Business Analytics in the Age of Generative AI

Curriculum

  • 5 Sections
  • 15 Lessons
  • 5 Days
Expand all sectionsCollapse all sections
  • Module 1: The Evolution of Business Analytics.
    3
    • 1.1
      From descriptive to predictive to generative analytics.
    • 1.2
      Generative AI: capabilities, models (e.g., GPT, DALL·E), and business impact.
    • 1.3
      Business analytics in the age of AI augmentation.
  • Module 2: Generative AI in Action.
    3
    • 2.1
      Automating data insights using natural language processing.
    • 2.2
      AI-assisted report generation, dashboards, and decision briefs.
    • 2.3
      Case studies: how companies are using GenAI in analytics today.
  • Module 3: Strategic Forecasting and Scenario Modelling.
    3
    • 3.1
      Predictive analytics powered by AI-generated simulations.
    • 3.2
      Demand planning, customer behaviour forecasting, and risk assessment.
    • 3.3
      Integrating GenAI outputs into business planning processes.
  • Module 4: Tools, Platforms, and Integration.
    3
    • 4.1
      Overview of GenAI-powered analytics platforms (Microsoft Copilot, Tableau GPT, etc.
    • 4.2
      API integration and plug-and-play analytics tools.
    • 4.3
      Workflow optimisation and cross-functional AI adoption.
  • Module 5: Governance, Ethics & Responsible Use.
    3
    • 5.1
      Ensuring data quality, accuracy, and model transparency.
    • 5.2
      Mitigating risks: hallucinations, bias, and over-reliance on AI.
    • 5.3
      Best practices for responsible deployment and team upskilling.
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