Skip to main content

ミッション

Data Scientist

Archived

8 モジュール

12 チャレンジ

9 時間 50 分

表示の対象:All users Applies to: Pega Customer Decision Hub 8.6

Gain a greater understanding of the key features, capabilities, and benefits of Prediction Studio. Prediction Studio is the dedicated workspace for data scientists to control the life cycles of predictions and the predictive models that drive them. Configure the predictions that are deployed in Customer Decision Hub™ to guide real-time customer interactions.

  • To receive updates to this mission follow uson twitter
  • Access the offline mission content here on twitter
初級
英語

このコンテンツは現在アーカイブされており、更新されていません。進捗状況は記録されません。Pega Cloudのインスタンスは無効となり、バッジは付与されなくなります。

Customer Decision Hub predictions

  • モジュール

    Customer Decision Hub predictions

    Archived

    5 トピック

    55 分

  • Familiarize yourself with the one-to-one customer engagement paradigm and discover how Pega's omni-channel AI delivers the right action during every...

Enabling AI in the NBA framework

  • モジュール

    Enabling AI in the NBA framework

    Archived

    5 トピック

    50 分

  • Learn how every next-best-action weighs customer needs against business objectives to optimize decisions based on priorities set by the business...

Adding predictors to an adaptive model

  • チャレンジ

    Adding predictors to an adaptive model

    Archived

    4 タスク

    10 分

  • U+ Bank is implementing cross-sell of their credit cards on the web by using Pega Customer Decision Hub™. The implementation team has set up the...

Monitoring adaptive models

  • モジュール

    Monitoring adaptive models

    Archived

    4 トピック

    50 分

  • It is a regular data scientist task to inspect the health of the adaptive models and share the findings with the business. The predictive performance...

Monitoring predictions

  • チャレンジ

    Monitoring predictions

    Archived

    4 タスク

    15 分

  • U+ Bank has recently implemented Pega Customer Decision Hub™ to display a personalized credit card offer to eligible customers on their website. The...

Monitoring adaptive models

  • チャレンジ

    Monitoring adaptive models

    3 タスク

    10 分

  • The U+Bank implementation for cross-sell on the web of their credit cards and the models have been learning for some time. Your task is to inspect the...

Exporting historical data

  • チャレンジ

    Exporting historical data

    4 タスク

    15 分

  • U+ Bank has implemented Pega Customer Decision Hub™ to display a personalized credit card offer to eligible customers on their website. As a data...

Creating and understanding decision strategies

  • モジュール

    Creating and understanding decision strategies

    4 トピック

    1時間 10 分

  • 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

  • チャレンジ

    Creating a decision strategy

    4 タスク

    25 分

  • As a Strategy designer, you are tasked to design a basic decision strategy that outputs the Label action with the lowest printing cost. A set of Label...

Testing a decision strategy

  • チャレンジ

    Testing a decision strategy

    4 タスク

    25 分

  • A decision strategy that produces the Next-Best-Label action has been set up. The main purpose of the decision strategy is to select the label with...

Creating predictions

  • モジュール

    Creating predictions

    Archived

    3 トピック

    35 分

  • Predicting customer churn is one among many business use cases involving predictive models. Pega Customer Decision Hub™ uses predictions that use...

Creating a churn prediction

  • チャレンジ

    Creating a churn prediction

    Archived

    2 タスク

    15 分

  • U+ Bank uses Pega Customer Decision Hub™ to personalize the credit card offer a customer is presented on their website. If a customer is eligible for...

Leveraging a churn prediction

  • チャレンジ

    Leveraging a churn prediction

    3 タスク

    25 分

  • U+ Bank uses AI to determine which credit card offers to show to customers on its website. The bank wants to reduce the number of clients that leave...

Creating predictive models

  • モジュール

    Creating predictive models

    5 トピック

    50 分

  • In Prediction Studio, three option to leverage historical data are available: creating models using Pega machine learning, importing models created in...

Building models with Pega machine learning

  • チャレンジ

    Building models with Pega machine learning

    Archived

    7 タスク

    5 分

  • U+ Bank uses artificial intelligence (AI) to determine which credit card offer to show a customer on the bank’s website. To reduce the number of...

Importing predictive models

  • チャレンジ

    Importing predictive models

    Archived

    2 タスク

    5 分

  • U+ Bank has recently implemented Pega Decision Management but has already been using predictive models created by an external bureau for some time...

MLOps

  • モジュール

    MLOps

    2 トピック

    25 分

  • Learn how to use Machine Learning Operations (MLOps) to replace the predictive model that drives a prediction with a new model. You can import a...

Replacing a predictive model

  • チャレンジ

    Replacing a predictive model

    3 タスク

    10 分

  • U+ Bank uses Pega Customer Decision Hub™ to personalize the credit card offers that a customer is presented on its website. To customers that are...

Text analytics for email routing

  • モジュール

    Text analytics for email routing

    Archived

    3 トピック

    35 分

  • 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

  • チャレンジ

    Training a topic model to improve email routing

    Archived

    3 タスク

    20 分

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

mission badge: Data Scientist

We'd prefer it if you saw us at our best.

Pega Academy has detected you are using a browser which may prevent you from experiencing the site as intended. To improve your experience, please update your browser.

Close Deprecation Notice