| Level | Topic | Type |
|---|---|---|
| 100 | Introduction to IBM Cloud Pak for Data | Article |
| 101 | Data Virtualization on IBM Cloud Pak for Data | Tutorial |
| 201 | Data visualization with Data Refinery | Tutorial |
| 202 | Find, prepare, and understand data with Watson Knowledge Catalog | Tutorial |
| 301A | Data analysis, model building, and deploying with Watson Machine Learning with notebook | Pattern |
| 301B | Automate model building with AutoAI | Tutorial |
| 301C | Build a predictive machine learning model quickly and easily with IBM SPSS Modeler | Tutorial |
| 401 | Monitoring the model with Watson OpenScale | Pattern |
For many industries, the journey to AI is a long-term strategy that's only beginning. In this learning path, we'll examine the case of a Telco company and use IBM Cloud Pak® for Data as the data and AI platform. We'll look at the process of collecting data, which can reside on multiple clouds, in various database formats, and with various needs for access control. In our Telco, we'll show how to organize the data with visualizations and other tools. Next, we'll look at the case of customer churn, and create a machine learning model that helps us to predict the risk that our Telco's clients will leave. Finally, we'll analyze the Telco's deployment of the machine learning model by looking at the model's performance, explainability, and fairness.
Part of this learning path explains how to use AutoAI in Watson Studio to automate the model building process. To learn more about AutoAI, look at the Simplify your AI lifecycle with AutoAI series.
To learn more about making deep learning and machine learning more accessible, explore Watson Machine Learning Accelerator. Discover how it provides an end-to-end, deep learning platform for data scientists
The learning path consists of step-by-step tutorials and patterns. To get started, click on a card below, or see the table above for a complete list of topics covered.
Introduction to IBM Cloud Pak for Data
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Learn about:
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Data Virtualization on IBM Cloud Pak for Data
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Learn about:
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Data visualization with Data Refinery
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Learn about:
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Find, prepare, and understand data with Watson Knowledge Catalog
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Learn about:
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Data analysis, model building, and deploying with Watson Machine Learning with notebook
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Learn about:
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Automate model building with AutoAI
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Learn about:
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Build a predictive machine learning model quickly with IBM SPSS Modeler
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Learn about:
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Monitoring the model with Watson OpenScale
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Learn about:
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