Complete Prompt Engineering Training

Master prompt engineering, GPT-4, and LangChain to build document analyzers & automation workflows.

What you’ll learn
Design powerful prompts for ChatGPT/GPT-4 using roles, context, constraints, and examples to reliably control output quality and style.
Summarize, rewrite, proofread, and structurally transform long documents, logs, and articles into clear, actionable formats.
Analyze and evaluate content (marketing pages, logs, reports) to extract pros/cons, patterns, gaps, and hidden insights using AI.
Apply reverse prompt engineering to deconstruct high-quality outputs and reconstruct optimized, reusable prompt formulas.
Use the OpenAI API to send structured chat/completion requests, handle parameters (model, temperature, max_tokens), and process responses in code.
Work with system/user/assistant roles, tokens, and context windows to design prompts that scale to longer, more complex tasks.

Requirements
Basic computer skills and the ability to comfortably use a web browser.

Description
Most people stop at “typing questions into ChatGPT.” This course is designed to take you far beyond that. You will learn how to think, design, and build like an AI workflow engineer using prompt engineering, the OpenAI API, and LangChain to solve real problems, not just generate pretty text.We start from absolute foundations: how LLMs work conceptually, what tokens and context windows are, and how roles (system, user, assistant) shape behavior. From there, you’ll learn to design prompts that are stable, repeatable, and controllable: role prompts, constraints, examples, few-shot patterns, chain-of-thought, structured outputs, tabular responses, and more.Once you can reliably control the model’s behavior, we move into serious, hands-on use cases: proofreading and transforming documents, extracting structured information from messy text, analyzing marketing pages and logs, and reverse prompt engineering existing content. You’ll see how to turn vague tasks into precise prompt recipes.Then we plug into the OpenAI API and LangChain. You’ll learn how to call GPT from Python, use PromptTemplate, build chains, wire in tools such as web search or file loaders, and finally use agents to automatically pick tools and plan actions. Together we’ll sketch mini-projects like document QA assistants, research helpers, and log analyzers.By the end of this course, you won’t just “use” ChatGPT you’ll know how to design prompts, APIs, and LangChain workflows that embed AI directly into your work, tools, and products.

Who this course is for
IT Professionals, System Administrators, and Support Engineers who want to use AI to summarize incidents, generate documentation, and accelerate troubleshooting.
Developers and DevOps/Platform Engineers who need to integrate GPT into scripts, backends, tools, and CI/CD or automation workflows.
Data Analysts, BI Engineers, and Data Engineers who want to use AI for log analysis, text preprocessing, insight extraction, and documentation generation.
Product Managers, Tech Writers, Educators, and Content Creators who want to draft, refine, and repurpose content faster with AI assistance.
Security and Operations teams who want structured AI help for reading large logs, reports, and system outputs.
Students and career switchers looking for a practical, project-oriented path into AI, LLMs, and prompt engineering.
Anyone who uses ChatGPT regularly and wants to move from “just chatting” to building serious, repeatable AI-powered workflows.

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