Creating, Testing, and Deploying Machine Learning Models with IBM Cloud Pak for Data V4.8

IBM Training for Creating, Testing, and Deploying Machine Learning Models with IBM Cloud Pak for Data V4.8

Skill Level: Intermediate

Modality: SPVC - Self Paced Virtual Class

Duration: 0.9 Day/s

Starting Price: $ - Contact for price

Overview:

This course focuses on the tools and services available in IBM Cloud Pak for Data 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 Cloud Pak for Data that can be used to build, test, and deploy machine learning models. 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 Cloud Pak for Data. Rather than teaching data science and machine learning, the course focuses on demonstrating how IBM 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 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

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Objective: Define a solution to a business problem using tools and frameworks from IBM Cloud Pak for Data

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 Cloud Pak for Data

Implement GitHub Integration and team collaboration in Cloud Pak for Data

Category: Data, Analytics, and AI

Product Name:

IBM Cloud Pak for Data

Badge and Certification Info:

Badge Title:

Badge ID: NONE

Brand: Cloud Pak for Data

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