This collection contains several basic courses that most AI Trainers should take as part of their onboarding. The courses in this collection will teach you how to build an AI agent, how to train it, how to improve it and how to write content. It might seem like a lot, but for the best learning experience, we recommend you not take everything at once. Instead, take what you need when you need it. The intention is that you should take this while working on an AI agent for the first time, taking the material you need when it's relevant and practicing what you've learned immediately.
Onboarding for AI Trainers
Introduction
Understand how this onboarding is structured and how to work with the content.
Building and training an AI agent
Everything you need to build an AI agent and train a custom NLU model. Even if you are not interested in building a model right away, we recommend the course on the intent hierarchy on its own as an introduction to creating content as well.
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Build an intent hierarchy
The intent hierarchy is the core of the boost platform. It is here that the scope, what your AI agent is supposed to know, is organized. This course covers how to build and navigate your own intent hierarchy.
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Train a prediction model
For the AI agent to understand end users it needs some kind of model, and the boost platform allows you to train your own custom NLU model. This course takes you through that process, including training data and test data.
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Intro to language processing
The language processing algorithm is a central part of how our custom NLU model understands languages. In this course, we will see how big of an impact this algorithm can have on model performance and how it works.
Improving an AI agent
These courses are about improving the model performance and prediction accuracy. If you want to go live with a very secure and high performing NLU model, then this is a must. These course will benefit from taking it slow, following the practical assignments and learning by doing.
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Improve the model with clean-up reports
The clean-up reports are built-in reports that tell you where to improve your trained NLU model. In this course, we will go through some of the more important reports and give you an idea of where to start.
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Improve the model with test results
Test results are the ultimate tool for benchmarking and improving a custom-trained NLU model. This course introduces the various kinds of issues we can find here and how to resolve them, improving prediction accuracy.
Creating content
Content, responses and conversation design is foundational to AI agents, and you need to know the basic tools. These courses covers the basics for both pre-defined responses and generated responses.
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Create and design basic content
An AI agent needs to be able to respond to an end user with well-designed and informative content. This course takes you through the most basic and simple tools for creating great responses.
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Build generative responses with gen action
Generative action allows us to create dynamic and flexible responses that cover multiple scenarios and use cases. This course gives an introduction to how to write instructions, upload knowledge, design action and API hooks, and set up guardrails, maki...
Analytics and conversation review
This course covers conversation review and it is the gateway into analytics. This is how you turn your AI agent's conversation logs into actionable insights, improving your AI agent as you go.
