Advanced prompt engineering techniques can significantly enhance the performance of language models by guiding them to generate more accurate, coherent, and relevant outputs. In this course, Prompt Engineering for Improved Performance, you’ll gain the ability to harness the capabilities of language models effectively, ensuring they align with specific use cases, minimize biases, and deliver high-quality outputs. First, you’ll journey beyond the realm of basic prompting techniques and learn how to leverage advanced prompting methods that elevate a model’s performance on reasoning tasks. Next, you’ll discover the art of prompt optimization for specific use cases by diving into optimization techniques for summarizing and expanding text, text-to-image generation, inferring sentiment, and transforming text from one format to another. Finally, you’ll gain insights into the key factors that impact the latency and performance of text generation models and explore mitigation techniques to improve performance. When you finish this course, you’ll have the knowledge of advanced prompt engineering techniques needed to harness the capabilities of language models effectively, ensuring they align with specific use cases, minimize biases, and deliver high-quality outputs.
Author Name: Kesha Williams
Author Description:
Kesha Williams is an award-winning technology leader with 25+ years of experience in tech. She’s passionate about hands-on building and developing the next generation of leaders. She’s versed in Java, AI/ML, and AWS and shares her knowledge with thousands of engineers around the globe through authoring courses, speaking at conferences, and writing technical blog posts.