Using Generative AI in technical writing (training course)

Comments from delegates

I’m happy to share that I’ve obtained a new certification: Using Generative AI in Technical Writing from Cherryleaf!..everything is explained from a tech comm perspective so it’s a bit easier to see how AI might be used.
Craig Wright

“Thanks for the great course! It was very comprehensive.”

N.B.

Topics covered

Introduction

ChatGPT and AI Basics

• What do the buzzwords mean?
• Using ChatGPT and similar tools – Software and Websites
• Prompt Engineering

Why use generative AI?

• Why use generative AI?
• The limitations of Large Language Models (LLMs) and AI systems
• Data security
• Legal considerations

Developing Content with AI Support

• A framework for using generative AI
• Using AI during the research stage of a documentation project
• Defining the goals and scope of a project with AI support
• Managing and automating a documentation project with AI support
  • The Model Context Protocol (MCP) and Autonomous AI agents
• Developing the information model
• Writing the content with AI support
• AI-enabled authoring tools
• About the temperature and top_p settings
• Reviewing content
• Maintaining your content

Publishing – Creating LLMs, enhanced search, and chatbots

• Publishing to chatbots and LLMs – Introduction
• Collecting the data to be used by a LLM or chatbot
• Creating a chatbot – The easy way (Retrieval-augmented generation (RAG))
• Using OpenAI GPTs chatbots
• Creating a chatbot – The more complex way (fine-tuning LLMs)
• The other type of chatbots
• AI and metrics
• AI and video walkthroughs

Advanced techniques

• Using custom profiles in ChatGPT
• The automated AI agent prompt
  • An automated AI agent for ChatGPT 4. It creates agents to assist users in achieving their goals.
• Useful Chrome extensions
• Inserting variable information into a prompt
  • Methods for personalising the responses for each user
• Adding user information and content from a repository into prompts
  • Methods for personalising the responses for each user
• Connecting chatbots and LLMs to data stored in an API
  • It’s now possible for an LLM to make calls to an API, and use the information returned from the API in its responses.
• Open Interpreter
  • Open Interpreter lets LLMs run code on your computer to complete tasks.
• Personalised learning techniques
  • Developing personalised learning plans from YouTube video content

Your project

Summary

• News
• Summary of course topics
• Action plans
• Course Resources for Further Learning

Duration and delivery format

Learning Materials

• The course comprises online training modules, which you can complete at your own pace. The course modules are delivered over the Web in small, manageable video presentations. You can pause the videos at any time and return to the course at times that suit you.
• We have provided a knowledge file. This knowledge file is a user guide for an imaginary application called ABC video player. Delegates can use this file when creating a chatbot if they don’t have their own content they can use.

Examples

• The modules describe practical examples and techniques you can use right away.

Demonstrations

• The modules contain demonstrations of the techniques and tools when they’re applied to technical writing.

Exercises

• You’ll be given exercises to work on throughout the course. This is a great way to put your learning to practice.
• You’ll get feedback on your final project from experts. You’ll discover what you’re doing right, and how you could make it even better.

Preview a module from the course