About this Course

Forbes AI stats* show that 86% of consumers prefer Humans to Chatbots. This means the consistency of AI-generated responses is crucial for building trust with users and maintaining brand reputation especially when chatbot industry is likely to reach $1.34 Billion in 2024. This Short Course was created to help AI developers, data scientists, and product managers accomplish the goal of achieving consistent and coherent responses from OpenAI\'s large language models. By completing this course, you\'ll be able to enhance the reliability of AI-generated responses, improve user satisfaction, and boost the overall performance of AI applications. You\'ll also gain practical techniques to ensure consistency in AI responses, allowing you to apply these skills immediately in your projects. More specifically, in this 2-hour long course, you will learn how to fine-tune OpenAI\'s large language models for specific contexts, apply post-processing techniques to refine responses, implement prompt engineering strategies for clear and effective communication, and analyze temperature and sampling parameters for optimal response consistency. This project is unique because it provides a comprehensive overview of strategies for achieving consistent responses with OpenAI\'s large language models, coupled with practical techniques and real-world examples. In order to be successful in this project, you will need a basic understanding of natural language processing and machine learning concepts.

Created by: Coursera Instructor Network