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Course Outline
Foundations of Generative Artificial Intelligence and Large Language Models
- Fundamental principles and historical development of generative AI
- Core concepts of Large Language Models (LLMs), including GPT and BERT architectures
- Distinctions between modern generative models and conventional Natural Language Processing (NLP) methodologies
Transformer Architectures and Model Training Methodologies
- Structural analysis of transformer frameworks within LLMs
- Mechanisms of self-attention and statistical language modeling
- Processes for pre-training, fine-tuning, and optimization of large-scale models
Prompt Engineering Strategies for Operational Efficiency
- Formulating structured prompts to ensure accuracy and relevance in model outputs
- Adapting prompt engineering techniques for diverse government operational requirements
- Iterative testing and optimization of prompt variations to enhance response quality
Deployment of LLMs in Public Sector Operations
- Leveraging conversational AI to streamline citizen service interactions
- Automating the generation of official communications and informational content
- Utilizing LLMs for data synthesis, analysis, and automated reporting
Ethical Standards, Bias Mitigation, and Accountability
- Detecting and assessing algorithmic biases in AI-generated content
- Navigating ethical frameworks and regulatory compliance in AI applications
- Establishing protocols for the responsible and accountable deployment of LLMs
Advanced Integration and Specialized Techniques
- Customizing LLMs for specialized governmental and public sector domains
- Integrating LLMs with existing IT infrastructures and AI systems for extended capability
- Evaluating multilingual support and cross-lingual communication capabilities
Future Trajectories of Generative AI in Government
- Analyzing emerging trends and research directions in generative AI
- Addressing scalability challenges and operational opportunities in public sector AI adoption
- Strategic planning for AI-driven modernization of government services
Executive Summary and Implementation Roadmap
Requirements
- Familiarity with core concepts in machine learning and natural language processing
- Working knowledge of Python programming and data structures
Target Audience
- Data scientists and AI engineers specializing in generative AI technologies
- Government professionals seeking to leverage automation and content generation for public service delivery
- Technical managers and strategic decision-makers tasked with integrating LLMs into official workflows
14 Hours
Testimonials (2)
the tips and recommended prompts that we can take away from this training
Lee Mei Lin - ST Engineering IHQ Pte Ltd
Course - InVideo AI: Creating Engaging Short-Form Videos
use of proper and effective prompt