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Course Outline
Introduction and Team Use Case Selection
- Overview of Artificial Intelligence in Industrial Environments
- Use Case Categories: Quality, Maintenance, Energy, and Logistics
- Team Formation and Scoping of Project Objectives for Government
Understanding and Preparing Industrial Data
- Types of Industrial Data: Time-Series, Tabular, Image, and Text
- Data Acquisition, Cleaning, and Preprocessing for Government Applications
- Exploratory Data Analysis Using Pandas and Matplotlib
Model Selection and Prototyping
- Choosing Between Regression, Classification, Clustering, or Anomaly Detection Models for Government Use Cases
- Training and Evaluating Models with Scikit-learn
- Utilizing TensorFlow or PyTorch for Advanced Modeling in Government Projects
Visualizing and Interpreting Results
- Creating Intuitive Dashboards and Reports for Government Decision-Makers
- Interpreting Performance Metrics: Accuracy, Precision, Recall
- Documenting Assumptions and Limitations in Government Contexts
Deployment Simulation and Feedback
- Simulating Edge/Cloud Deployment Scenarios for Government Operations
- Collecting Feedback and Improving Models for Government Use
- Strategies for Integrating AI Solutions with Existing Government Operations
Capstone Project Development
- Finalizing and Testing Team Prototypes for Government Applications
- Peer Review and Collaborative Debugging in a Government Setting
- Preparing Project Presentations and Technical Summaries for Government Audiences
Team Presentations and Wrap-Up
- Presenting AI Solution Concepts and Outcomes to Government Stakeholders
- Group Reflection and Lessons Learned in a Government Context
- Roadmap for Scaling Use Cases Within Government Organizations
Summary and Next Steps
Requirements
- An understanding of manufacturing or industrial processes for government applications.
- Experience with Python and basic machine learning techniques.
- Ability to work with both structured and unstructured data.
Audience
- Cross-functional teams within the public sector.
- Engineers for government projects.
- Data scientists supporting governmental initiatives.
- IT professionals in federal, state, and local agencies.
21 Hours
