Train ML Models for Document Understanding

Specialized AI has demonstrated its value in enterprise automation scenarios. With the reliable and scalable automation architecture and the addition of high-performing machine learning models, automation developers can build high value document understanding automations. 

This course is about how to get to these high-performing machine learning models. You'll start by understanding the out-of-the-box ML models offered by UiPath, then how to gather the requirements for the ML models, then how to select the best documents for training, then how to actually do the pre-labeling, labeling, training, and deploying the ML model. You'll be using the UiPath Document Understanding and AI Center first-party services. 

The course has been built with the help of the most experienced practitioners from UiPath, part of the UiPath Technology Services team. You'll get a lot of videos in which the steps are demonstrated by one of our Senior Solution Architects. There are best practices guides awaiting at the end of the course, and there are tons of practice opportunities. 

This course is designed to cater to automation professionals looking to become Specialized AI Professionals able to generate value across the entire cycle: in building the automation project, as well as getting the best ML models. 

The Train ML Models for Document Understanding course is an advanced level course. It takes about 5 hours to complete. At the end, you’ll receive a diploma of completion. 

To make the most of this learning experience, we recommend you going through the following learning plans and courses: 

• The Automation Explorer learning plan 

• The Automation Developer Associate learning plan 

• The UiPath Document Understanding Overview course 

• The UiPath AI Center course

The course is aimed at automation developers looking to become proficient with specialized AI and document understanding.

The full agenda covers:  

• Introduction to model-based extraction 

• The out-of-the-box ML models for document understanding 

• Gather the requirements for the ML extractor 

• Select the documents and label the data 

• Train and deploy the ML model 

• Use the ML skill in Studio 

• Build a model with Forms AI 

At the end of the course, you should be able to: 

• Describe how the model-based extraction works in comparison to the rule-based extraction. 

• List the steps of preparing and deploying a custom ML extractor. 

• Gather the requirements for an ML extractor. 

• Select the right documents for labeling and training the ML model. 

• Set up and use Document Manager for pre-labeling and labeling. 

• Import, store and categorize documents in Document Manager. 

• Use pre-labeling and labeling in Document Manager. 

• Train an ML model in AI Center. 

• Deploy an ML model as an ML skill. 

• Use the ML skill in UiPath Studio.