Mission
AI for 1:1 Customer Engagement
10 Modules
19 Challenges
12 hrs 35 mins
Familiarize yourself with the one-to-one customer engagement paradigm and discover how Pega omni-channel AI delivers the right action during every customer interaction. Learn how to optimize the adaptive models that drive Pega Customer Decision Hub™ predictions. Learn how to use predictive models to improve the decisions that Customer Decision Hub makes and how to update predictions with the MLOps process.
Available in the following mission:
Customer Decision Hub overview
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Module
Customer Decision Hub overview
5 Topics
55 mins
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Familiarize yourself with the one-to-one customer engagement paradigm and discover how Pega’s omnichannel AI delivers the right action during every...
Exploring decisions in Customer Decision Hub
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Challenge
Exploring decisions in Customer Decision Hub
4 Tasks
10 mins
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U+ Bank uses Pega Customer Decision Hub™ to decide which one of four credit card offers to show in a web banner when a customer logs in to the U+ Bank...
Customer Decision Hub predictions
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Module
Customer Decision Hub predictions
2 Topics
30 mins
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Discover the Pega Customer Decision Hub™ predictions in the Prediction Studio portal, a comprehensive workspace for data scientists who manage...
Exploring Prediction Studio
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Challenge
Exploring Prediction Studio
2 Tasks
10 mins
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U+ Bank implements Pega Customer Decision Hub™ to optimize customer interactions on their web channel by showing a personalized web banner when...
Adaptive models
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Module
Adaptive models
3 Topics
40 mins
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Online, adaptive models are crucial to next-best-action decision strategies in Pega Customer Decision Hub™. Adaptive Decision Manager is a key...
Adding predictors to an adaptive model
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Challenge
Adding predictors to an adaptive model
6 Tasks
10 mins
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U+ Bank is implementing cross-selling of their credit cards on the web by using Pega Customer Decision Hub™. The implementation team has set up the...
Monitoring adaptive models
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Module
Monitoring adaptive models
3 Topics
40 mins
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It is a regular data scientist task to inspect the health of the out-of-the-box Pega Customer Decision Hub™ predictions and the adaptive models that...
Monitoring adaptive models
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Challenge
Monitoring adaptive models
3 Tasks
10 mins
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The models for the U+Bank implementation of cross-selling on the web of their credit cards have been learning for some time. Your task in this...
Exporting adaptive model data
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Module
Exporting adaptive model data
3 Topics
35 mins
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The reporting datamart of Pega Adaptive Decision Manager (ADM) is an open data model. As a result, data scientists that work on Pega Customer Decision...
Exporting historical data
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Challenge
Exporting historical data
2 Tasks
15 mins
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U+ Bank has implemented Pega Customer Decision Hub™ to display a personalized credit card offer to eligible customers on their website. As a data...
Exporting adaptive model data for external analysis
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Challenge
Exporting adaptive model data for external analysis
3 Tasks
25 mins
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U+ Bank implements cross-selling of their credit cards on the web by using Pega Customer Decision Hub™. Self-learning, adaptive models drive the...
Creating predictions
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Module
Creating predictions
6 Topics
1 hr
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Predicting customer churn is one of many business use cases that involve predictive models. Pega Customer Decision Hub™ provides predictions that use...
Creating a churn prediction using a scorecard
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Challenge
Creating a churn prediction using a scorecard
3 Tasks
20 mins
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U+ Bank wants to predict and avoid potential customer churn before it happens. When customers leave a bank, the result is costly in terms of lost...
Building models with Pega machine learning
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Challenge
Building models with Pega machine learning
6 Tasks
15 mins
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U+ Bank implements Customer Decision Hub™ to determine which credit card offer to show a customer on the bank's website. To reduce the number of...
Importing predictive models
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Challenge
Importing predictive models
1 Task
10 mins
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U+ Bank implements Pega Decision Management but already uses predictive models that an external bureau created. You are asked to make an existing H2O...
Creating a churn prediction using an ML model
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Challenge
Creating a churn prediction using an ML model
2 Tasks
15 mins
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U+ Bank implements Pega Customer Decision Hub™ to personalize the credit card offer a customer is presented on their website. If a customer is...
MLOps
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Module
MLOps
3 Topics
30 mins
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In the ever-evolving world of data-driven decisions, organizations aim to refine predictive models for optimal outcomes. This involves challenging...
Shadowing an adaptive model
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Challenge
Shadowing an adaptive model
4 Tasks
10 mins
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U+ Bank uses Pega Customer Decision Hub™ to personalize the credit card offers that a customer receives on the U+ Bank website. A prediction...
Challenging a Predictive Model
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Challenge
Challenging a Predictive Model
3 Tasks
10 mins
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U+ Bank uses Pega Customer Decision Hub™ to personalize the credit card offers that a customer receives on the U+ Bank website. The bank makes a...
Creating and understanding decision strategies
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Module
Creating and understanding decision strategies
4 Topics
1 hr 10 mins
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Next-Best-Action Designer provides a guided and intuitive UI to bootstrap your application development with proven best practices that generate the...
Creating a decision strategy
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Challenge
Creating a decision strategy
3 Tasks
25 mins
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As a Decisioning Architect, you are tasked with designing a basic decision strategy that outputs a Label action with the lowest printing cost. A set...
Testing a decision strategy
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Challenge
Testing a decision strategy
3 Tasks
25 mins
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A decision strategy that produces the next-best-label action is set up in the application. The purpose of the decision strategy is to select the label...
Defining prediction patterns
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Module
Defining prediction patterns
2 Topics
20 mins
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Learn how to improve the predictive power of your adaptive models by configuring additional potential predictors in Pega Customer Decision Hub™. For...
Using behavioral data as predictors
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Challenge
Using behavioral data as predictors
4 Tasks
10 mins
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U+ Bank is implementing cross-selling of their credit cards on the web by using Pega Customer Decision Hub™. All available customer data, including...
Using offline model scores as predictors
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Challenge
Using offline model scores as predictors
3 Tasks
15 mins
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U+ Bank uses Pega Customer Decision Hub™ for engagement with its customers. Externally, the data scientist team produces many product group scores for...
Using online model scores as predictors
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Challenge
Using online model scores as predictors
4 Tasks
15 mins
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U+ Bank is implementing cross-selling of its products on the web by using Pega Customer Decision Hub™. The U+ Bank data science team develops...
Leveraging a churn prediction
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Challenge
Leveraging a churn prediction
3 Tasks
25 mins
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U+ Bank implements Customer Decision Hub™ to determine which credit card offers to show to customers on its website. As part of the implementation...
Model governance
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Module
Model governance
4 Topics
50 mins
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AI has the potential to deliver significant benefits, but improper controls can result in regulatory issues, public relations problems, and liability...
Detecting unwanted bias in engagement policy conditions
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Challenge
Detecting unwanted bias in engagement policy conditions
6 Tasks
15 mins
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U+ Bank is currently cross-selling on the web by showing various credit cards to its customers.
The bank wants to run an ethical bias simulation in...
