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Duration 7 hours
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
Summary and Next Steps
Using Prompts for Code Explanation and Debugging
Crafting 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
- Translating natural language into structured SQL queries
- Structuring outputs for seamless integration into test suites
- Clarifying legacy or unfamiliar code
- Requesting logic walkthroughs or edge case analysis
- Identifying and explaining bugs or inefficiencies
- Producing code from plain-language descriptions
- Controlling output format and programming language
- Handling complex logic or multiple functions
- Enhancing results through prompt chaining and feedback loops
- Error recovery and prompt tuning strategies
- Case studies on refinement for technical tasks
- Prompt libraries and reuse patterns
- Utilizing prompt templates in VS Code or API-based workflows
- Assessing prompt quality and performance in production environments
- Grasping prompts, context, tokens, and models
- Prompt types: zero-shot, one-shot, few-shot
- Applying system vs. user instructions across different APIs
Requirements
Target Audience
- Developers utilizing LLMs for code generation or analysis
- Technical leads exploring AI tools within their workflows
- Software professionals testing LLM integrations
- Background in software development or scripting
- Knowledge of common programming languages (e.g., Python, JavaScript, SQL)
- Fundamental understanding of large language models and AI tools such as ChatGPT, Claude, or Copilot
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
