Course Outline
Best Practices and Tooling
Common Pitfalls and Mitigation Strategies
Introduction to Prompt Engineering
Prompt Refinement and Iterative Design
Prompting for Test Automation and SQL Generation
Conclusion and Next Steps
Using Prompts for Code Explanation and Debugging
Writing Prompts for Code Generation
- Preventing hallucinated code or security vulnerabilities
- Managing incomplete or ambiguous inputs
- Establishing safe fallback prompts and guardrails
- Deriving test cases from requirements or existing code
- Creating structured SQL queries from natural language descriptions
- Structuring outputs for seamless integration into test suites
- Explaining legacy or unfamiliar code segments
- Prompting for logic walkthroughs or edge case analysis
- Identifying and explaining bugs or performance inefficiencies
- Generating code from plain-language specifications
- Directing output format and programming language selection
- Handling complex logic or multi-function structures
- Enhancing outcomes via prompt chaining and feedback loops
- Error recovery and prompt tuning techniques
- Case studies on refinement for technical tasks
- Prompt libraries and reusable patterns
- Utilizing prompt templates in VS Code or API-based workflows
- Assessing prompt quality and performance in production environments
- Grasping the concepts of prompts, context, tokens, and models
- Prompt variations: zero-shot, one-shot, and few-shot
- Differentiating between system and user instructions across various APIs
Requirements
Target Audience
- Developers leveraging LLMs for code creation or analysis
- Technical leads investigating AI tools within their workflows
- Software professionals exploring LLM integration capabilities
- Background in software development or scripting
- Proficiency in standard programming languages (e.g., Python, JavaScript, SQL)
- Foundational knowledge of large language models and AI tools such as ChatGPT, Claude, or Copilot
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 1600 € + VAT*
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Testimonials (1)
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny
