Fundamentals of Prompt Engineering for ChatGPT and LLMs

About this course

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 LLMs (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 & TheoryModern 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 & instructor feedback sessions

Performance tuning and evaluation exercises

Core modules (7)Module 1 — ChatGPT & 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<

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