Creating, Testing, and Deploying Machine Learning Models with IBM Watson Studio – W7L149GCR

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Course Code: W7L149G Brand: IBM Cloud Pak for Data Category: Analytics Skill Level: Intermediate Duration: 7H Modality:CR      Audience

Data Scientists and Business Analysts


The data scientists’ and business analysts’ prerequisite skills and knowledge include: 

  • Experience working in a browser  
  • Some experience writing and running Python programs 
  • Some experience with the Jupyter Notebook environment  
  • Some experience working with a graphical user interface (GUI) 
  • Knowledge of machine learning (regression, decision trees, and random forests) 
  • Some experience working with GitHub

  Short Summary

This course focuses on the tools and services available in IBM Watson Studio that can be used to build, test, and deploy machine learning models.  Overview

This course takes the data scientist (or business analyst) on a journey from the creation of several machine learning models to its deployment and testing. Various tools and services as well as programming and graphical user interfaces are used in the process. The course ends with the sharing of assets on GitHub and a brief discussion on governance and stewardship. 


  • Introduction
  • Rapid prototyping with AutoAI
  • Creating, testing, and deploying machine learning models
  • Governance, integration, and collaboration


  • Define a solution to a business problem using tools and frameworks from IBM Watson Studio 
  • Demonstrate how the AI lifecycle can be automated by building a rapid prototype using AutoAI 
  • Build, train, and deploy a machine learning model with the tools and services available in Watson Studio 
  • Implement GitHub Integration and team collaboration in Watson Studio
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