Since the release of ChatGPT, Dolly, PaLM, and other large language models (LLMs), an increasing number of companies are seeking to leverage these technologies to address business-specific or industry-specific problems. A challenge many organizations face is optimizing LLMs to adequately meet unique demands while also ensuring ethical compliance. In this course, Optimize LLMs for Specific Business Needs, you will gain the ability to tailor LLMs to accomplish specific business challenges and objectives. First, you’ll explore the role of LLMs in addressing business opportunities and learn how they can be tailored to meet industry requirements. Next, you’ll discover the intricacies involved in adapting, fine-tuning, and optimizing models for specific use cases, including methods for integrating domain-specific knowledge into LLMs and several techniques for optimizing computation and memory utilization of these models in production environments. Finally, you’ll learn testing and validation strategies for LLMs in business applications and how to continuously refine LLMs based on real world-usage. When you’re finished with this course, you’ll have the skills and knowledge of LLMs needed to effectively integrate these tools into your organization.
Author Name: Daryle Serrant
Author Description:
Daryle has worked as a data scientist and software engineer for industry giants such as Tesla and Lockheed Martin, as well as companies in the Aerospace and Defense, Consumer Electronics, Health and Wellness, and Renewable Energy sectors. He excels in leveraging machine learning to automate and streamline operations, and has crafted software products spanning the technology spectrum, from web and mobile applications to embedded systems. Amid his ventures in the tech world, Daryle discovered a pr… more

Table of Contents

• Course Overview
  1min
• Model Adaptation and Fine-tuning LLMs for Business Needs
  11mins
• LLM Optimization, Testing, and Validation Techniques
  19mins