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Course Outline
Introduction and Team Use Case Selection
- Overview of Artificial Intelligence (AI) in industrial environments
- Use case categories: quality assurance, maintenance optimization, energy efficiency, logistics management
- Team formation and definition of project objectives for government applications
Understanding and Preparing Industrial Data
- Types of industrial data: time-series, tabular, image, text
- Data acquisition, cleaning, and preprocessing techniques for government use
- Exploratory data analysis using Pandas and Matplotlib to support public sector workflows
Model Selection and Prototyping
- Selecting appropriate models: regression, classification, clustering, or anomaly detection for government projects
- Training and evaluating models with Scikit-learn to meet public sector standards
- Leveraging TensorFlow or PyTorch for advanced modeling in government applications
Visualizing and Interpreting Results
- Creating intuitive dashboards and reports for government stakeholders
- Interpreting performance metrics such as accuracy, precision, and recall to ensure accountability
- Documenting assumptions and limitations to support transparent governance
Deployment Simulation and Feedback
- Simulating edge and cloud deployment scenarios for government systems
- Collecting feedback from public sector users to refine models
- Strategies for integrating AI solutions into existing government operations
Capstone Project Development
- Finalizing and testing team prototypes for government use cases
- Peer review and collaborative debugging to ensure robustness and reliability
- Preparing project presentations and technical summaries for government stakeholders
Team Presentations and Wrap-Up
- Presenting AI solution concepts and outcomes to public sector audiences
- Group reflection on lessons learned and best practices for government
- Developing a roadmap for scaling use cases within the organization for government operations
Summary and Next Steps
Requirements
- A foundational knowledge of manufacturing or industrial processes
- Experience with Python and fundamental machine learning techniques
- Proficiency in handling both structured and unstructured data
Audience for Government
- Cross-functional teams within government agencies
- Engineers employed by federal, state, and local governments
- Data scientists working in public sector roles
- IT professionals supporting government operations
21 Hours
