ChatGPT for Real-World Applications From Prompts to Product

What you'll learn
Understand how ChatGPT and large language models actually work, including their capabilities, limitations, and real-world risks, so they can be used responsibly
Design reliable and structured prompts that produce consistent, controllable outputs suitable for real business and engineering use cases.
Move beyond chatbots to build production-ready ChatGPT applications, using APIs, tool-calling, and multi-step workflows.
Integrate ChatGPT with external data using Retrieval-Augmented Generation (RAG) to reduce hallucinations and generate grounded, auditable responses.
Design and evaluate ChatGPT system architectures, considering latency, cost, scalability, and failure-tolerant workflows.
Apply testing, monitoring, and evaluation techniques to ensure AI outputs remain accurate, reliable, and trustworthy in production environments.
Address real-world concerns such as bias, privacy, and compliance, including safe handling of sensitive data and human-in-the-loop validation.
Build and present a complete ChatGPT-powered application, demonstrating the ability to take an idea from prompt design to production-ready deployment.
Requirements
Basic familiarity with using ChatGPT or similar AI tools
General understanding of how software or business workflows operate
Curiosity about AI systems, automation, or real-world applications
Willingness to think beyond simple prompts and chat interfaces
Description
"This course contains the use of artificial intelligence"ChatGPT has moved far beyond simple chatbots and demos, but most people are still using it in ways that do not translate to real business or production environments. This course is designed to close that gap. ChatGPT for Real-World Applications: From Prompts to Production teaches you how to use ChatGPT the way it is actually applied in modern organizations - as part of reliable systems, data pipelines, and production-ready workflows.You will start by building a clear understanding of what Large Language Models (LLMs) really are, what ChatGPT can and cannot do, and why prompting alone is not enough for real-world use. From there, the course progressively moves into prompt engineering fundamentals, advanced reliability techniques, and structured prompt workflows that reduce hallucinations and inconsistent outputs.As you advance, you will learn how ChatGPT is integrated into business analytics, engineering automation, and internal tooling, including how to design prompts that support decision-making, reporting, and code assistance without introducing risk. A major focus of the course is Retrieval-Augmented Generation (RAG), where you will learn how to safely connect ChatGPT to your own data, databases, and documents so outputs are grounded, traceable, and auditable.The course then shifts into system design and architecture, teaching you how to place ChatGPT within real applications using APIs, tool-calling, and multi-step workflows. You will learn how to handle latency, cost control, scaling, and failure-tolerant design, ensuring your applications can operate reliably under real usage conditions.You will also cover AI safety, bias, and privacy, including PII handling, compliance considerations, and human-in-the-loop validation, so your systems can be trusted by users and stakeholders. Finally, the course emphasizes testing, monitoring, and evaluation, treating ChatGPT like any other production software component, not a black box.By the end of the course, you will complete a capstone project where you design, build, evaluate, and present a production-ready ChatGPT application, demonstrating your ability to move from idea to deployment with confidence.What You'll Gain from This CourseBy completing this course, you will:Understand how ChatGPT actually works and where it fits in real systemsDesign reliable prompts that produce consistent, controlled outputsMove beyond chatbots to build production-grade ChatGPT applicationsIntegrate ChatGPT using APIs, tools, and retrieval systems (RAG)Reduce hallucinations through structured workflows and grounding techniquesDesign scalable and cost-aware architecturesApply testing, monitoring, and evaluation strategies for AI systemsBuild trustworthy, auditable, and compliant AI solutionsGain real-world, job-ready skills used by engineers, analysts, and product teamsThis course is ideal if you want to use ChatGPT professionally, build AI-powered systems, or advance your career by learning how generative AI is actually deployed in modern organizations - not just experimented with.
Who this course is for
Developers and software engineers who want to integrate ChatGPT into real applications, workflows, and production systems using APIs, tools, and structured architectures.
Data analysts, data engineers, and analytics professionals who want to use ChatGPT for reporting, insight generation, internal assistants, and data-driven decision support.
Product managers, technical leads, and founders who need to design, evaluate, and ship AI-powered features responsibly and effectively.
Business professionals and operations teams who want to automate workflows, improve productivity, and understand how ChatGPT can be safely deployed in real business environments.
Students and career switchers who want job-ready, real-world skills in generative AI beyond simple prompt writing.
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