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Mission

Pega NLP Essentials

3 Modules

4 Challenges

2 hrs 55 mins

Pega Customer Decision Hub 8.7
Visible to all users
Beginner Pega Customer Decision Hub 8.7 English

Better understand the key features and benefits of Pega Natural Language Processing (NLP). Use Pega NLP to analyze and extract meaningful information from text by using text analytics to improve business performance and customer experience.
Text predictions use natural language processing to analyze incoming messages in conversational channels, such as email or chat. These predictions can help you in a variety of ways:

  • Route emails to the right department
  • Create the right case type while auto-populating relevant properties based on extracted entities
  • Respond to users with relevant messages.

In this mission, you will learn how to train a text prediction to detect topics, extract entities, and identity the sentiment for incoming emails or chat messages.

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Pega AI overview

  • Module

    Pega AI overview

    2 Topics

    35 mins

  • Prediction Studio is the dedicated workspace for data scientists to control the life cycles of predictions and the predictive models that drive them...

Text analytics for email routing

  • Module

    Text analytics for email routing

    3 Topics

    35 mins

  • Humans can effortlessly interpret a single tweet but are unable to parse a large volume of information efficiently. Businesses are exploring ways to...

Training a topic model to improve email routing

  • Challenge

    Training a topic model to improve email routing

    4 Tasks

    20 mins

  • U+ Bank plans to use Pega Customer Service™ to route incoming emails to the appropriate department based on the topic of the email. For several use...

Using entity extraction with chatbot channel

  • Module

    Using entity extraction with chatbot channel

    1 Topic

    15 mins

  • Better understand the key features and benefits of entity extraction with chatbot channel. Use this module to learn how to enable the chatbot to...

Creating a chatbot channel

  • Challenge

    Creating a chatbot channel

    5 Tasks

    15 mins

  • U+ Air wants to use a chatbot to handle ticket cancellation requests through all relevant channels to reduce the workload of customer service...

Creating entity extraction model using Ruta script

  • Challenge

    Creating entity extraction model using Ruta script

    6 Tasks

    20 mins

  • U+ Air uses a chatbot to serve its customers. Currently, the chatbot recognizes when a customer wants to cancel a ticket, and the system automatically...

Enhancing entity extraction with machine learning

  • Challenge

    Enhancing entity extraction with machine learning

    5 Tasks

    25 mins

  • The U+ Air chatbot channel detects U+ Air ticket numbers using a RUTA-based model. The current entity model recognizes a ticket number in the...

Pega NLP Essentials

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