ChatGPT for Real-World Applications: From Prompts to Product

Introduction

This course, “ChatGPT for Real-World Applications: From Prompts to Production,” is for professionals who want to use ChatGPT beyond demos. It suits developers, data people, product managers, operations teams, and learners moving into AI roles. You will learn how LLMs work, design reliable prompts, build production-ready ChatGPT applications with APIs and tool-calling, integrate external data safely, and operate models with testing, monitoring, and human oversight.

What you’ll learn

• Explain how large language models (LLMs) and ChatGPT generate text and where they fail.
• Design reliable, structured prompts that produce consistent, controllable outputs for business tasks.
• Build API-driven ChatGPT applications, including tool-calling and multi-step workflows.
• Implement Retrieval-Augmented Generation (RAG) to ground responses in external data and reduce hallucinations.
• Design system architectures that balance latency, cost, and scalability while remaining failure-tolerant.
• Apply testing, monitoring, and evaluation to maintain output accuracy and trustworthiness in production.
• Handle bias, privacy, PII, and compliance with human-in-the-loop validation practices.

Who this is for

• Developers and software engineers integrating ChatGPT into production systems.
• Data analysts and data engineers using ChatGPT for reporting and decision support.
• Product managers, technical leads, and founders designing AI-powered features responsibly.
• Business professionals and operations teams automating workflows and internal tools.
• Students and career switchers seeking practical, job-ready generative AI skills.

Prerequisites

• Basic familiarity with using ChatGPT or similar AI tools. General understanding of how software or business workflows operate.

Course overview

This course takes you from understanding LLM fundamentals to delivering production-ready ChatGPT applications. It begins by explaining what LLMs can and cannot do, and why simple prompting is not enough for reliable business use. You then learn prompt engineering fundamentals and advanced techniques to reduce inconsistent outputs. The curriculum covers integrating ChatGPT with company data using Retrieval-Augmented Generation so responses are grounded and auditable. The later sections focus on system design: using APIs and tool-calling, building multi-step workflows, and addressing latency, cost, and scaling. The course also covers safety topics such as bias, privacy, PII handling, compliance, and human review. Practical modules on testing and monitoring ensure you treat AI as a production component. A capstone project helps you build and present a complete ChatGPT-powered application.

Syllabus highlights

• LLM fundamentals: capabilities, limitations, and risks.
• Prompt engineering: structured prompts and reliability patterns.
• RAG: connecting documents, databases, and audit trails.
• APIs & tool-calling: building multi-step application flows.
• System design: latency, cost, scalability, and failure tolerance.
• Testing & monitoring: evaluation metrics and production checks.
• Safety & compliance: bias mitigation, PII handling, and human-in-the-loop.

How to Enrol / Claim Free Access

1. Find the course page on the provider site (Data Science Academy or partner pages).
2. Review the course overview, syllabus highlights, and prerequisites.
3. Click Enrol or Register and follow the checkout steps.
4. Check the price at checkout, free status can change.

Free status can change anytime. Please verify the price on the enrollment/checkout page.

Tips to complete faster

• Follow a 4-week plan: Week 1 — LLM basics and prompt patterns; Week 2 — RAG and data integration; Week 3 — APIs, tool-calling, and architecture; Week 4 — testing, safety, and capstone work.
• Set aside 60–90 minutes daily for hands-on labs and coding exercises.
• Use small projects: build one RAG prototype and one API integration to reinforce learning.
• Join study groups or peer reviews to speed up feedback on prompts and designs.

FAQ

• Is it really free? Not specified. Free status can change; check the checkout page before relying on a free offer. Free status can change anytime. Please verify the price on the enrollment/checkout page.
• Will I get a certificate? Not specified.
• How long will it stay free? The free status can change at any time. Always verify the current price on the enrolment or checkout page.
• Do I need coding skills? The course is practical and assumes basic familiarity with AI tools; specific coding requirements are Not specified.

Conclusion

This course helps you shift from informal ChatGPT use to building reliable, auditable AI features in production. Key takeaways are understanding LLM behavior, designing structured prompts, integrating data with RAG, and operating systems that are safe, scalable, and monitored. Verify the course price before enrolling since free access is not guaranteed. Join our WhatsApp group for free course alerts