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Generative AI

Learn by Doing - Prompt Engineering 101

Craft impactful AI interactions with confidence! Join 'Prompt Engineering 101' - where you'll master the art of crafting precise prompts for AI communication, empowering you to navigate the world of AI effortlessly and unleash innovation
Vijin Palazhi
HashiCorp and CNCF Trainer
DevOps Pre-Requisite Course
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What you’ll learn

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Description

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.

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What our students say

About the instructor

Vijin Palazhi is the Chief Technology Officer at KodeKloud, with over a decade of experience in IT infrastructure and expertise in systems engineering. 

His skills encompass storage and backup solutions, Oracle Engineered Systems Stack, Oracle Middleware, virtualization, containerization (Kubernetes and Docker Swarm), and automation. 

Vijin has specialized in Oracle Stack, particularly in Exalogic ODA Exadata and Oracle Virtual Machine Storage and Backup. 

He also has extensive experience with storage technologies, CI/CD, cloud platforms (AWS/Oracle Cloud), data center operations, and server management.

About the collaborator

Srinivas is a DevOps Lab Engineer at Kodekloud. He believes in continuous learning and has interests around DevOps, Cloud, Containers and automation. He is also an Open Source Advocate and a Kubesimplify ambassador, and he loves to share his knowledge with people.

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This course comes with hands-on cloud labs
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