Overview
“Learn by Doing – Prompt Engineering 101” offers a structured, interactive approach to learning the fundamentals of prompt engineering with AI. This course centers on an application built to interact with the widely-used, open-source Mixtral-8x7B model through a ChatGPT-style interface, aiming to equip participants with the ability to create impactful communication prompts for AI interactions. Through a series of practical labs, learners will explore various strategies to obtain relevant, accurate, and nuanced responses from AI. This course is suitable for a wide audience, including those new to AI and professionals looking to enhance their interaction capabilities with advanced technologies.
Course Structure:
Introduction to AI Chatbot Interaction:
- Begin with an open sandbox lab to get acquainted with the chatbot’s interface and the basic principles of AI communication. This initial exploration sets the groundwork for more detailed prompt crafting.
Labs Overview:
- Detailing for Clarity: Techniques to include precise details in your prompts, aiming to improve the relevance and precision of AI responses.
- Persona Play: Strategies for crafting prompts that prompt the AI to assume various personas, making its responses more adaptable to different contexts.
- Delimiters: Understanding how to use delimiters to clearly separate parts of a complex query, helping the AI to organize its responses more effectively.
- Step-by-Step Clarification: Breaking down complex tasks into simpler, actionable steps within prompts to guide the AI’s assistance in a structured manner.
- Illustrating Through Examples: The practice of using examples within prompts to direct the style or format of AI responses, ensuring they meet specific requirements.
- Specifying Output Length: How to instruct the AI on the desired length of its responses to fit various information needs and presentation formats.
Model Limitations:
The course utilizes the Mixtral-8x7B model, emphasizing its open-source accessibility with some operational limitations for fair use:
- 30 Requests Per Minute (RPM): A limit on the interaction rate to prevent overloading the system.
- 14,400 Requests Per Day (RPD): A daily cap on queries to ensure all users have access to the service.
- 40,000 Tokens Per Minute (TPM): A boundary on the volume of text processed per minute to maintain efficient service delivery.
Conclusion:
“Learn by Doing – Prompt Engineering 101” equips participants with the fundamental skills in prompt engineering necessary for effective AI communication. This course lays the groundwork for applying these skills across various domains, such as research, creative endeavors, programming, and more. With the capability to construct precise and meaningful prompts, participants will be able to unlock new possibilities in productivity and innovation, making the most of their interactions with AI technology.
