This comprehensive course by IBM explores the fundamental principles and advanced techniques of prompt engineering in generative AI. Learn to create effective prompts, leverage tools like IBM watsonx Prompt Lab, and apply techniques such as Interview Pattern, Chain-of-Thought, and Tree-of-Thought to enhance the reliability and quality of large language models (LLMs).
Join this course to gain valuable insights from practitioners and optimize your prompt engineering skills for generative AI models.
Certificate Available ✔
Get Started / More Info
This course comprises modules that cover the concept and relevance of prompt engineering, common techniques and approaches, and hands-on labs to enhance your prompt engineering skills in generative AI models.
This module introduces the concept and relevance of prompt engineering in generative AI models. Learn best practices for creating impactful prompts and explore common prompt engineering tools. The hands-on labs offer practical experience in optimizing results through effective prompts in the IBM Generative AI Classroom.
Delve into common prompt engineering techniques and approaches such as Text-to-Text, Interview Pattern, Chain-of-Thought, and Tree-of-Thought. Gain practical experience with hands-on labs to apply these techniques effectively and learn about the future of human-crafted prompts.
This module provides an opportunity to test your knowledge and skills through a final project, applying prompt engineering techniques and best practices. Obtain an IBM Cloud Feature Code, activate a trial account, and explore IBM watsonx Prompt Lab to enhance your understanding of generative AI prompt engineering.
This Natural Language Processing course equips you with the skills to design NLP applications, perform sentiment analysis, build chatbots, and translate languages....
Deep Learning with PyTorch: Build an AutoEncoder
Introduction to Trading, Machine Learning & GCP is a comprehensive course covering the fundamentals of trading, quantitative trading strategies, and application...
Learn about sample-based learning methods in reinforcement learning, including Monte Carlo and temporal difference learning, and how to combine model-based planning...