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Course Outline
Day 1: Foundations of AI and Its Capabilities in Understanding Documents for Government
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Module 1: Introduction to AI for Professionals
- Clarifying AI, ML, and NLP: A straightforward explanation without technical jargon.
- AI as a Supportive Tool: Transitioning the perspective from threat to assistance.
- Successful Case Studies: Real-world examples of how other sectors (legal, finance) utilize AI.
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Module 2: Core NLP Capabilities for Document Analysis
- Document Classification: Training AI to automatically categorize document types (e.g., Deed of Establishment, Financial Reports, Environmental Permits).
- Entity Extraction: Instructing AI to identify and extract specific information from text, such as directors' names, investment values, effective dates, or Tax ID numbers.
- Sentiment Analysis & Risk Identification: Detecting potentially risky clauses or sentiment within documents.
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Module 3: Machine Learning Concepts in Practice
- How Machines "Learn": The concept of supervised learning using existing document examples.
- The Importance of Quality Data: Ensuring accurate and reliable data for AI applications.
- The ML Project Lifecycle: From data collection to model evaluation.
Day 2: Practical Applications, Tools, and Strategic Planning
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Module 4: Workshop - Mapping Your Work to AI Solutions
- Interactive Session: Identifying the most time-consuming manual tasks in the licensing process.
- Brainstorming: Exploring how NLP and ML can address these challenges.
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Module 5: The Landscape of AI Technology and Tools
- Understanding Different Tiers of Tools: From off-the-shelf software-as-a-service (SaaS) to customizable platforms.
- Live Demonstration: Showcasing several AI tools for document analysis.
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Module 6: Designing and Implementing an AI Project
- Steps to Initiate a Pilot Project.
- Defining Success Metrics (time efficiency, error reduction).
- The "Human in the Loop" Role: Emphasizing the importance of expert verification.
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Module 7: Ethical Considerations and Risk Management
- Data Security and Confidentiality in AI Systems.
- Potential Bias in AI Models and Mitigation Strategies.
- Building Trust in AI Analysis Results.
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Module 8: Summary and Action Plan Development
- Drafting an Action Plan for AI Implementation in the Licensing Division.
- Final Discussion and Q&A.
Requirements
Audience for Government
- Licensing Division
- Documentation Staff
14 Hours
Testimonials (1)
Training and examples
