NEOPOLIS AKADEMY
Prompt Engineering with the OpenAI API
Practical approach to prompt engineering for the OpenAI API: instruction design, context management, chain-of-thought and reusable templates. Provides methods to design, test and iterate reliable prompts for production use.
View this course on Akademy ↗Enrolment and practical details are available on Neopolis Akademy.
What you will explore
Covers structuring clear instructions, controlling output formats and reducing hallucinations through prompt design.
Presents patterns (examples, templates, few-shot, chain-of-thought) and how to adapt them to varied goals.
Addresses context management: windowing, memory recall, and techniques to preserve important information.
Provides an experimentation and iterative evaluation methodology to improve prompt robustness and consistency.
STEP BY STEP
Course programme
01Prompt Engineering with the OpenAI API
Structured approach to prompt engineering for the OpenAI API: message roles, implementing a get_response() function, zero/one/few‑shot strategies and output structure control. Applied to summaries, product descriptions and chatbot development.
Sets out fundamentals: API message roles and building a get_response() function to orchestrate calls.
Explains prompting strategies (zero/one/few‑shot) and using few‑shot prompts for tasks like sentiment analysis.
Applies techniques to concrete cases: market‑report summaries, product description expansion, and behavioral control of chatbots.
Explore this module on Akademy ↗Programme source: Neopolis Akademy. Original course page