Mission
AI for 1:1 Customer Engagement
10 Modules
20 Challenges
13 hrs 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.
Available in the following mission:
Customer Decision Hub overview
-
Module
Customer Decision Hub overview
3 Topics
30 mins
-
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
-
Challenge
Exploring decisions in Customer Decision Hub
4 Tasks
10 mins
-
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
-
Module
Customer Decision Hub predictions
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...
Exploring Prediction Studio
-
Challenge
Exploring Prediction Studio
4 Tasks
10 mins
-
U+ Bank implements Pega Customer Decision Hub™ to optimize customer interactions on their web channel by showing a personalized web banner when...
Adaptive models
-
Module
Adaptive models
5 Topics
55 mins
-
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
-
Challenge
Adding predictors to an adaptive model
6 Tasks
10 mins
-
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
-
Module
Monitoring adaptive models
3 Topics
40 mins
-
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
-
Challenge
Monitoring predictions
6 Tasks
15 mins
-
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
-
Challenge
Monitoring adaptive models
3 Tasks
10 mins
-
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
-
Module
Exporting adaptive model data
3 Topics
35 mins
-
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
-
Challenge
Exporting historical data
5 Tasks
15 mins
-
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
-
Challenge
Exporting adaptive model data for external analysis
4 Tasks
25 mins
-
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
-
Module
Creating predictions and predictive models
6 Topics
1 hr 5 mins
-
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
-
Challenge
Building models with Pega machine learning
6 Tasks
15 mins
-
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
-
Challenge
Importing predictive models
1 Task
10 mins
-
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
-
Challenge
Creating a churn prediction using an ML model
2 Tasks
15 mins
-
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
-
Module
MLOps
6 Topics
1 hr
-
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
-
Challenge
Adding predictors to an adaptive model in BOE
5 Tasks
10 mins
-
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
-
Challenge
Replacing a predictive model
3 Tasks
10 mins
-
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
-
Challenge
Promoting a shadow model to active status
5 Tasks
10 mins
-
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
-
Module
Creating and understanding decision strategies
4 Topics
1 hr 10 mins
-
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
-
Challenge
Creating a decision strategy
3 Tasks
25 mins
-
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
-
Challenge
Testing a decision strategy
3 Tasks
25 mins
-
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
-
Module
Defining prediction patterns
2 Topics
20 mins
-
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
-
Challenge
Using behavioral data as predictors
3 Tasks
10 mins
-
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
-
Challenge
Using model scores as predictors
4 Tasks
15 mins
-
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
-
Challenge
Leveraging a churn prediction
3 Tasks
25 mins
-
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
-
Module
Model governance
4 Topics
50 mins
-
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
-
Challenge
Detecting unwanted bias in engagement policy conditions
7 Tasks
15 mins
-
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...