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Course Outline

  • Introduction to AI and its role in the manufacturing industry
  • Data-driven productivity: how AI can optimize production processes
  • Collecting and organizing data for KPI analysis
  • AI models for demand forecasting and predictive maintenance
  • Analyzing production line performance and detecting anomalies
  • Generating reports and dashboards for KPI monitoring
  • Best practices for data-driven and AI-supported decision-making

Expected outcomes:

  • Understanding of core AI concepts and their application in manufacturing
  • Ability to analyze data and KPIs using AI
  • Creation of integrated reports and dashboards for performance monitoring
  • Optimization of processes and support for data-driven operational decisions

Requirements

  • Understanding of: core AI concepts, data analysis, and KPI reporting in manufacturing
  • Experience with: production data, Excel, visualization tools, and reporting platforms
  • Programming experience: basic Python or R skills for AI applications (optional)
  • Target audience: production engineers, data analysts, operational managers, process specialists

 

  • Covered topics: productivity and process optimization with AI
  • Covered topics: industrial data reporting and analysis
  • Covered topics: dashboard generation and data-driven decision-making
 7 Hours

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