Watson Studio Methodology - eLearning (W7067G-WBT)


In this course, you will explore data preparation, data modeling, data visualization, and data cataloging using Watson Studio, Watson Knowledge Catalog, and Watson Machine Learning.


Data scientists, data engineer, business analyst




  • Data science and AI
  • Watson Studio
  • Watson Machine Learning
  • Watson Knowledge Catalog
  • Data refinement
  • Data modeling
  • Data science with notebooks
  • Model deployment
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Course Outline

Data science and AI 
• Describe the value of artificial intelligence 
• Explain the AI ladder approach and AI lifecycle 
• Identify the roles for working with data and AI 

Watson Studio 
• Summarize the benefits of Watson Studio 
• Outline the integration of Watson Studio and Watson Machine Learning 
• List and explain the tools available in Watson Studio 
• Sign up for a free IBM Watson account 

Watson Machine Learning 
• Describe machine learning methods and how they fit with AI 
• Create a Watson Studio project for learning models 

Watson Knowledge Catalog 
• Explain the features of Watson Knowledge Catalog 
• Identify the role of data policies to govern data assets 
• List and describe the data files used in this course 
• Create a catalog, add assets to a catalog, and add catalog assets to a project 

Data refinement 
• List the steps to successful data mining 
• Describe the typical customer churn business problem 
• Identify the steps in the data refinement process 
• Shape a data set using the Data Refinery according to specific observations 

Data modeling 
• Differentiate the Watson Studio tools to create models 
• Create a Watson Machine Learning model using AutoAI 
• Create a Machine Learning model using SPSS Modeler 
• Build a model using SparkML Modeler Flow 

Data science with notebooks 
• Experiment with Jupyter notebooks 
• Load from a file and run a Jupyter notebook with Watson Studio 

Model deployment 
• Identify the model repository 
• List model deployment and test options 
• Deploy a model 
• Test a deployed model