Course Outline
Introduction to Prompt Engineering
- Definition of prompt engineering and its operational significance for government entities.
- Application scenarios and potential efficiency gains in public sector workflows.
- Summary of standard large language model behaviors and limitations.
Fundamental Guidelines for High-Quality Prompts
- Strategies for ensuring clarity, providing adequate context, setting constraints, and incorporating examples.
- Techniques for regulating response length, structure, and tone.
- Identification of common errors and methods for their prevention.
Standardized Prompting Frameworks and Templates
- Development of instruction-driven and role-based prompts.
- Implementation of chain-of-thought and sequential processing methods.
- Utilization of few-shot learning techniques and reusable template structures.
Practical Prompting Activities
- Formulating prompts for document summarization and text revision.
- Structuring prompts for data classification and information extraction tasks.
- Real-time refinement: Adjusting prompts based on initial model outputs.
Assessment and Optimization of Prompts
- Criteria and practical heuristics for assessing prompt effectiveness.
- Application of testing scenarios and edge cases to verify prompt robustness.
- Protocols for version control and documentation of prompt modifications.
Security, Bias Mitigation, and Ethical Governance
- Detection and mitigation of biased or non-compliant model outputs.
- Establishment of fundamental safeguards and content restrictions.
- Determination of appropriate instances for mandatory human oversight.
Conclusion, Reference Materials, and Future Actions
- Provision of quick-reference guides and standardized templates.
- Curation of recommended literature and professional community resources.
- Recommendations for sustained professional development and advanced learning trajectories.
Requirements
- Basic experience with web-based artificial intelligence chat interfaces
- Fundamental knowledge of natural language processing concepts
- Proficiency in iterative problem-solving approaches
Target Audience
- Entry-level staff seeking to develop effective communication strategies with AI models
- Product managers, content specialists, and data analysts integrating AI tools into their workflows
- Personnel tasked with generating, reviewing, or evaluating AI-generated content for public use
Testimonials (2)
The interactive style, the exercises
Tamas Tutuntzisz
Course - Introduction to Prompt Engineering
Since we had a Roche internal AI Training (6 lections), the presented majority content was a good sum-up, however, personally I did learn something new in this training session, which was to counter back the prompt, so the AI program has to ask you about possible questions regarding to this specific topic.
