Prompt Engineering and LLM Application Design
Learn design principles and refactoring practices that improve maintainability. The course focuses on structure, trade-offs, and long-term code quality. AI is part of the course workflow throughout.
Course Overview
- Design principles and refactoring practices that improve maintainability.
- Structure, trade-offs, and long-term code quality.
Who Should Attend
- Developers, senior developers, and technical leads.
- Teams that want a practical conversation about structure and maintainability.
- Learners who need to recognize design smells and refactoring opportunities.
Prerequisites
Participants should have:
- working familiarity with the target language, framework, or platform
- basic comfort using AI tools is helpful but not required unless specified
- basic troubleshooting skills
- access to the required tools or accounts before class
What You'll Learn
By the end of this course, participants will be able to:
- use AI tools in the normal development workflow
- design practical AI-enabled application experiences
- evaluate output quality and failure modes
- apply guardrails, documentation, and governance habits
- move from experiment to a production-minded implementation plan
What the Course Covers
In Scope:
- AI-assisted development workflows
- prompting and model use
- evaluation and quality controls
- guardrails and production concerns
Not Covered:
- deep model training and research
- math-heavy ML theory unless requested
- enterprise governance beyond the course scope
Course Outline
- Unit 1: Foundations:
- core concepts and terminology
- Unit 2: Application:
- guided practice and labs
- Unit 3: Handoff:
- troubleshooting, review, and next steps
Hands-On Work
Representative Labs:
- build a simple AI-assisted workflow
- test prompts and outputs
- evaluate quality and edge cases
- adjust guardrails for a team use case
Practice and Discussion:
- Guided practice with checkpoints
- Scenario discussion using realistic examples
- Review of trade-offs and next steps
Environment and Tools
- Access to the chosen AI tool or platform
- Browser, editor, and lab environment
- Sample app or notebook workspace
- Optional enterprise policy guidance
Customization Options
- role-based track variations
- industry or domain-specific examples
- mixed-experience pacing adjustments
- accelerated or extended delivery formats
Next Steps
- production AI engineering path
- AI security follow-on
- agentic AI specialization
- team rollout and governance workshop
Related training topics
Justify your training
Use this sample request letter — copy it into an email to your manager and personalize the bracketed details to make the case for the time and budget.
Sample training request letter
Subject: Request for AI & AI Security training from Applied Technology Academy
[Decision Maker Name],
I'm writing to request time and budget approval to complete Applied Technology Academy's course, Prompt Engineering and LLM Application Design. The information below outlines how this training benefits our organization, the tasks I'll be able to perform after completing it, and relevant cost and funding details.
Course Description
Learn design principles and refactoring practices that improve maintainability. The course focuses on structure, trade-offs, and long-term code quality. AI is part of the course workflow throughout. Applied Technology Academy is an award-winning, SBA-certified woman-owned training provider (est. 2008) whose instructors are active practitioners; the course is hands-on with virtual labs and a learn-by-doing methodology.
Course Objectives
Once I've completed the course, I'll be able to:
- By the end of this course, participants will be able to:
- use AI tools in the normal development workflow
- design practical AI-enabled application experiences
- evaluate output quality and failure modes
- apply guardrails, documentation, and governance habits
- move from experiment to a production-minded implementation plan
Expected Organizational Benefits
After completing this course, I will be better equipped to apply these skills directly to our projects, reduce our reliance on outside expertise, strengthen our team's capabilities, and share what I learn with colleagues.
Expected Cost & Funding
Course fee: [request an itemized quote at the link below]. Applied Technology Academy supports multiple funding paths that may reduce or cover this cost: GSA MAS purchasing and government purchase orders, military credentialing funding (Army CA, AF COOL, CG COOL), VA GI Bill and VR&E, ATA Flexible Spending, and student financing. Private team cohorts are available if colleagues should attend with me.
Conclusion
This training provides practical, hands-on experience I can apply immediately to strengthen our work in ai & ai security. Additional course information is available at https://appliedtechnologyacademy.com/prompt-engineering-and-llm-application-design/.
Thank you for your consideration,
[Your Name]
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