Fundamentals of Prompt Engineering for ChatGPT and LLMs

Course overview Transform how you communicate with large language models. This intensive, hands-on program teaches the principles and practice of prompt engineering for modern LL Ms (ChatGPT, GPT-4 and similar models). Learners will master a proven set of techniques to reliably shape outputs, extract high-value insights, and optimize model performance for real-world tasks.Why this course Practical focus: workshops, real-world case studies, and iterative feedback cycles.Framework-driven: learn a repeatable prompt-design method (instruction, context, examples, persona, format, tone) to improve consistency and control Tool-ready: apply techniques across ChatGPT/GPT-4 and complementary AI tools used in industry workflows Course structure Foundation &amp; Theory Modern LLM architectures and capabilities (ChatGPT, GPT-4, distinctions from GPT-3.5)Core prompt engineering principles and behavioral mechanics Contextual conversation design and session-state management Response quality metrics and performance boundaries Practical Applications Hands-on prompt-crafting labs with iterative testing and evaluation Industry-specific use cases (marketing, product, data, support, engineering)Peer review &amp; instructor feedback sessions Performance tuning and evaluation exercises Core modules (7)Module 1 — ChatGPT &amp; LLM EssentialsLLM architectures, strengths, and limitations Model behavior, safety considerations, and hallucination mitigation Module 2 — Engineering Fundamentals Core prompt-building blocks and decomposition Output-targeting techniques and common pitfalls Module 3 — Context Mastery<