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Duration 7 hours
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
- Production line performance analysis and anomaly detection
- Generating reports and dashboards for KPI monitoring
- Best practices for data-driven and AI-based decision-making
Expected outcomes:
- Understanding basic AI concepts and applying them in manufacturing
- The ability to analyze data and KPIs using AI
- Creating integrated reports and dashboards for performance monitoring
- Optimizing processes and supporting data-driven operational decisions
Requirements
- Understanding of: basic AI concepts, data analysis, and KPI reporting in manufacturing
- Experience with: production data, Excel, and visualization and reporting tools
- Programming experience: basic knowledge of Python or R for AI applications (optional)
- Target audience: production engineers, data analysts, operations managers, and process specialists
- Topics covered: Productivity and process optimization with AI
- Topics covered: Reporting and industrial data analysis
- Topics covered: Dashboard generation and data-driven decision-making
