Creating, Testing, and Deploying Machine Learning Models with IBM Watson Studio V4.8

Creating, Testing, and Deploying Machine Learning Models with IBM Watson Studio V4.8

 

IBM Training for Creating, Testing, and Deploying Machine Learning Models with IBM Watson Studio V4.8

Skill Level: Intermediate

Modality:  CR - Classroom based Trainng or ILO - Instructor Led Online Class

Duration: 0.9 Day/s

Starting Price:  $ - Contact for price

Overview:

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.

The focus of this course is on the tools and services available in IBM Watson Studio that can be used to build, test, and deploy machine learning models on Cloud Pak for Data V4.8. It 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.


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Target Audience:

The course is designed for Data Scientists and Business Analysts. It caters to aspiring or practicing Data Scientists, and Business Analysts with prior knowledge of Data Science and Machine Learning, but lacking familiarity with IBM tools and IBM Watson. Rather than teaching data science and machine learning, the course focuses on demonstrating how IBM Watson tools and services can address significant business challenges, targeting professionals at the associate level and beyond..

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Prerequisites: Before taking this course, you should have:Knowledge of Data Science

  • Knowledge of Machine Learning
  • Experience with the Python programming language
  • .

    Topic: IntroductionDiscuss the four steps that make up the AI Ladder

  • Explain the AI Lifecycle and the different personas that are involved in an AI project
  • Explain the components that comprise a Watson Studio project
  •  Rapid prototyping with AutoAIDescribe the benefits of AutoAI for rapid prototyping
  • Discuss the steps needed to run a successful AutoAI experiment
  • Interpret and discuss the results from an AutoAI experiment
  •  Creating, testing, and deploying machine learning modelsDiscuss various ways of building a machine learning model in Watson Studio by using programming and visual interfaces
  • Discuss the contents of the model repository
  • Describe the various deployment methods for AI models
  •  Governance, integration, and collaborationDescribe the capabilities and features to support governance of your data 
  • Describe the team collaboration features of Watson Studio
  • .

    IBM Training

    Objective: 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
  • Category: Data, Analytics, and AI

     

    Product Name:

    IBM Watson Studio Premium Cartridge for IBM Cloud Pak for Data

     

    Badge and Certification Info:

    Badge Title: Creating, Testing, and Deploying Machine Learning Models with IBM Watson Studio V4.8 - Code: W7L549G

    Badge ID: 6b400cd2-c4ce-4a71-901f-7112a3f0e917

     

    Brand: Cloud Pak for Data

     

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    Replaced By: 

    This is an updated course that provides a hands-on model building experience.

    W7L549 W7L149 Python Jupyter Notebook

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