Mission
AI for 1:1 Customer Engagement
10 Modules
20 Défis
13 heures 25 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.
Disponible dans la mission suivante :
Customer Decision Hub overview
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Module
Customer Decision Hub overview
3 Rubriques
30 mins
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Familiarize yourself with the one-to-one customer engagement paradigm and discover how Pega's omni-channel AI delivers the right action during every...
Exploring decisions in Customer Decision Hub
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Défi
Exploring decisions in Customer Decision Hub
4 Tâches
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 Rubriques
35 mins
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Prediction Studio is the dedicated workspace for data scientists to control the life cycles of predictions and the predictive models that drive them...
Exploring Prediction Studio
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Défi
Exploring Prediction Studio
4 Tâches
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
5 Rubriques
55 mins
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Online, adaptive models play a crucial part in Pega Customer Decision Hub™ next-best-action decision strategies. These models drive the predictions...
Adding predictors to an adaptive model
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Défi
Adding predictors to an adaptive model
6 Tâches
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 Rubriques
40 mins
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Data scientists must regularly inspect the health of the out-of-the-box Pega Customer Decision Hub™ predictions and the adaptive models that drive...
Monitoring predictions
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Défi
Monitoring predictions
6 Tâches
15 mins
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U+ Bank uses Pega Customer Decision Hub™ to display a personalized credit card offer to eligible customers on their website. The bank now wants a...
Monitoring adaptive models
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Défi
Monitoring adaptive models
3 Tâches
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 Rubriques
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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Défi
Exporting historical data
5 Tâches
15 mins
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U+ Bank implements Pega Customer Decision Hub™ to display a personalized credit card offer to eligible customers on their website. As a data scientist...
Exporting adaptive model data for external analysis
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Défi
Exporting adaptive model data for external analysis
4 Tâches
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 and predictive models
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Module
Creating predictions and predictive models
6 Rubriques
1h 5 mins
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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
Building models with Pega machine learning
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Défi
Building models with Pega machine learning
6 Tâches
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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Défi
Importing predictive models
1 Tâche
10 mins
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U+ Bank has recently implemented Pega Decision Management, but already uses predictive models that an external bureau created. You are asked to make...
Creating a churn prediction using an ML model
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Défi
Creating a churn prediction using an ML model
2 Tâches
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
6 Rubriques
1h
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Machine Learning Operations (MLOps) is an approach that streamlines the process of building, testing, and deploying machine learning models. As a data...
Adding predictors to an adaptive model in BOE
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Défi
Adding predictors to an adaptive model in BOE
5 Tâches
10 mins
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U+ Bank uses Pega Customer Decision Hub™ to personalize the credit card and mortgage offers that customers receive on its website. To optimize...
Replacing a predictive model
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Défi
Replacing a predictive model
3 Tâches
10 mins
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U+ Bank uses Pega Customer Decision Hub™ to personalize the credit card offers that a customer receives on its website. The bank makes a proactive...
Promoting a shadow model to active status
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Défi
Promoting a shadow model to active status
5 Tâches
10 mins
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U+ Bank uses Pega Customer Decision Hub™ to personalize the credit card offers that customers receive on its website. The bank makes a proactive...
Creating and understanding decision strategies
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Module
Creating and understanding decision strategies
4 Rubriques
1h 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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Défi
Creating a decision strategy
3 Tâches
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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Défi
Testing a decision strategy
3 Tâches
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 Rubriques
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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Défi
Using behavioral data as predictors
3 Tâches
10 mins
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U+ Bank is implementing cross-sell of their credit cards on the web by using Pega Customer Decision Hub™. All available customer data, including...
Using model scores as predictors
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Défi
Using model scores as predictors
4 Tâches
15 mins
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U+ Bank is implementing cross-selling of its credit cards on the web by using Pega Customer Decision Hub™. To further enhance the predictive power of...
Leveraging a churn prediction
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Défi
Leveraging a churn prediction
3 Tâches
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 Rubriques
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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Défi
Detecting unwanted bias in engagement policy conditions
7 Tâches
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...