Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 7 hours
Course Outline
Best Practices and Tooling
Common Challenges and Mitigation Tactics
Introduction to Prompt Engineering
Prompt Refinement and Iterative Design
Prompting for Test Automation and SQL Generation
Conclusion and Future Directions
Utilizing Prompts for Code Explanation and Debugging
Crafting Prompts for Code Generation
- Preventing the creation of hallucinated code or security vulnerabilities
- Managing incomplete or ambiguous inputs
- Designing secure fallback prompts and guardrails
- Deriving test cases from requirements or existing code
- Constructing structured SQL queries from natural language descriptions
- Formatting outputs for seamless integration into test suites
- Clarifying legacy or unfamiliar codebases
- Requesting logic walkthroughs or edge case analyses via prompting
- Identifying and explaining bugs or inefficiencies
- Generating code from plain-language descriptions
- Controlling output format and selecting programming languages
- Handling complex logic or multi-function interactions
- Enhancing outcomes through prompt chaining and feedback loops
- Strategies for error recovery and prompt tuning
- Case studies focused on refining prompts for technical tasks
- Leveraging prompt libraries and reuse patterns
- Implementing prompt templates in VS Code or API-based workflows
- Assessing prompt quality and performance in production scenarios
- Comprehending prompts, context, tokens, and model mechanics
- Types of prompts: zero-shot, one-shot, and few-shot
- Applying system versus user instructions across different APIs
Requirements
Target Audience
- Developers utilizing LLMs for code generation or analysis
- Technical leads investigating AI tools for workflow integration
- Software professionals exploring LLM integrations
- Prior experience in software development or scripting
- Familiarity with standard programming languages such as Python, JavaScript, and SQL
- A foundational understanding of large language models and AI tools like 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
