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Prompt Engineering for Non-Technical Professionals

Two Hour Targeted Topic

Course Summary

This Targeted Topic is designed to provide an understanding of the concepts of prompt engineering and the use of Large Language Models (LLMs) and Natural Language Processing (NLP). It will provide Non-Technical Professionals with a foundation for creating appropriate and contextually relevant prompt engineering questions.for various business contexts.

Purpose
Understand the concepts of prompt engineering and the use of Large Language Models (LLMs) and Natural Language Processing (NLP).
Prerequisites
In order to succeed in this course, you should have an interest in understanding how prompt engineering can drive innovation in business with innovative Generative AI.
Role
Non-Technical Professionals
Skill level
Beginner
Style
Targeted Topic
Duration
2 hours
Related technologies
AI/ML | Gen AI

 

Productivity objectives
  • Describe Generative AI and Prompt Engineering
  • Identify Use Cases
  • Discuss creating effective prompts
  • Identify ethical considerations

What you'll learn:

In this course, you'll learn:
  • Generative AI and Prompt Engineering
    • What is Generative AI and How is it Relevant for Business?
    • What is Prompt Engineering?
    • The Role of Large Language Models (LLM)
  • How to Leverage Prompt Engineering?
    • The Importance of Prompt Engineering
    • Crafting and Designing the Right Questions
    • How it advances Generative AI
  • Identifying Use Cases for Non-Tech Professionals
    • Creating content and copywriting
    • Customer support and communication
    • Automated note-taking
    • Idea generation and problem-solving
    • Learning and knowledge retrieval
    • Others
  • Creating Effective Prompts
    • Asking the Right Questions
      • Be creative
      • Be Specific and Clear
      • Define clear goals
      • Craft specific prompts
      • Experiment with variations
    • Examples
      • Instructor-generated examples for different use cases
      • Demo with audience participation
    • Avoiding Pitfalls and Miscommunication
  • Ethical Considerations
    • Addressing bias and fairness in Generative AI applications.
    • Navigating legal and ethical implications.
    • Ensuring transparency and accountability.

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