Duration: 2 days


This Generative AI Prompt Engineering training course teaches students how to design and refine prompts for natural language processing (NLP) models. Students learn how to select the right inputs, questions, and context to ensure that the model generates accurate and relevant outputs. There is also a focus on prompt engineering for generative NLP models such as GPT (Generative Pre-trained Transformer).


  • Understand the importance of prompt engineering in NLP models
  • Learn the different types of prompts and their use cases
  • Develop skills to design and refine prompts for NLP models


No prior experience is presumed.


Anyone writing or composing copy or wanting to produce more effective written work, including emails.

Outline for Prompt Engineering: Techniques and Best Practices Training

  • Chapter 1: Introduction to AI Language Models and Prompt Engineering
    • Overview of AI language models
    • Introduction to Prompt Engineering
    • Importance of Prompt Engineering in AI applications
  • Chapter 2: Understanding the Prompt
    • Types of prompts
    • Components of a prompt
    • Factors affecting prompt effectiveness
  • Chapter 3: Techniques for Crafting Effective Prompts
    • Designing prompts for clarity
    • Leveraging context and examples
    • Balancing brevity and detail
  • Chapter 4: Restricting ChatGPT's Answers to Your Own Document Corpus
    • Setting up a custom document corpus
    • Techniques for guiding AI model focus
    • LLM focus and attention, and GPT3 vs GPT4 differences
    • Ensuring relevant and accurate outputs
  • Chapter 5: Generating Synthetic Data and Images
    • Crafting prompts for CSV data generation
    • Formatting AI outputs for data visualization
    • Prompt engineering for SVG image generation
    • GPT4 SVG images vs DALL-E image generation
  • Chapter 6: Language Translation and Slide Creation
    • Designing prompts for language translation
    • Ensuring translation accuracy and fluency
    • Generating slides using markdown and Prompt Engineering
  • Chapter 7: Prompt Engineering for Various Applications
    • Creative writing and content generation
    • Question-answering and information retrieval
    • Data processing and transformation
  • Chapter 8: Iterative Prompt Refinement
    • Analyzing AI model outputs
    • Techniques for prompt iteration and improvement
    • Incorporating user feedback into prompt design
  • Chapter 9: Group Project: Applying Prompt Engineering to Real-world Scenarios
    • Identify a problem that can be solved using AI language models
    • Design and refine prompts to achieve desired outcomes
    • Present project outcomes and Prompt Engineering process
  • Chapter 10: Ethics and Best Practices in Prompt Engineering
    • Ethical considerations for AI language model usage
    • Ensuring data privacy and security
    • Best practices for Prompt Engineering in professional settings
01/01/2024 - 01/02/2024
10:00 AM - 06:00 PM
Eastern Standard Time
Online Virtual Class
USD $1,525.00
02/12/2024 - 02/13/2024
10:00 AM - 06:00 PM
Eastern Standard Time
Online Virtual Class
USD $1,525.00
03/18/2024 - 03/19/2024
10:00 AM - 06:00 PM
Eastern Standard Time
Online Virtual Class
USD $1,525.00