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Course Outline
Module 1: Understanding Prompting in IT Contexts
- Defining prompting and its significance for IT work.
- How AI models process context, instructions, and role definitions.
- Key components of a prompt: intent, role, context, constraints, and format.
- Common prompting errors and strategies to avoid them.
Module 2: Structured Prompting Techniques
- Implementing frameworks such as Role–Task–Format, Chain-of-Thought, and Few-Shot prompting.
- Developing reusable prompt templates for routine IT tasks.
- Designing system-level and task-specific prompts.
Module 3: IT Use Cases and Hands-On Practice
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Writing and optimizing prompts for:
- System troubleshooting and diagnostics.
- Configuration and deployment documentation.
- Code review and script generation.
- Client communication and knowledge base updates.
- Iterating and validating prompts to ensure accuracy and consistency.
Module 4: Integrating Prompting into IT Workflows
- Incorporating AI prompting into IT service management and consulting processes.
- Managing prompt libraries, versioning, and documentation.
- Ensuring ethical and secure use of AI in enterprise environments.
- Next steps: exploring advanced prompting tools and automation frameworks.
Conclusion and Q&A
- Recap of key concepts.
- Group reflection on best practices and lessons learned.
- Practical takeaways for continued skill development.
Requirements
- Basic understanding of IT concepts, system workflows, or technical documentation.
- Prior experience using AI tools (such as ChatGPT, Copilot, or similar platforms) in professional settings.
Audience
- IT consultants.
- System administrators.
- Technical project managers.
- Solution designers specializing in AI-enabled systems.
7 Hours
Testimonials (2)
The interactive style, the exercises
Tamas Tutuntzisz
Course - Introduction to Prompt Engineering
A great repository of resources for future use, instructor's style (full of good sense of humor, great level of detail)
