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Watson Studio Methodology - eLearning
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 science and AI
- Watson Studio
- Watson Machine Learning
- Watson Knowledge Catalog
- Data refinement
- Data modeling
- Data science with notebooks
- Model deployment
Data scientists, data engineer, business analyst
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
Self-Paced Training Info
Learn at your own pace with anytime, anywhere training
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Self-Paced Training Terms & Conditions
IBM Web Based Training courses are sold on a per-user basis. WBT courses provide a training advantage for you and your teams, helping you get up to speed quickly. Take the courses you need, at your convenience and at your own pace.
You can start the course at any time within 12 months of enrolling for the course. After you register/start the course, you have 30 days to complete your course. Within this 30 days, the self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours a day.
System RequirementsTo participate in this course, the student workstation must meet the following hardware requirements:
- Minimum of 256 MB of memory
- Windows Vista or Windows 7-10 (32-bit or 64-bit edition)
- Internet Explorer 6 or higher or Firefox ESR
- 128-bit encryption
- Citrix Receiver for connection to the IBM Remote Lab Platform
- Access to Internet with at least 128 kbps down and 128 kbps up
- Other platforms/combinations may work but are not officially supported by IBM.
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