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Course Description

This Integrated Analytics System course teaches data scientists how to use the data science capabilities of IBM Integrated Analytics System, using Watson Studio, RStudio, Spark, and in-database analytics. 

Objectives

Unit 1: Introduction to IBM Integrated Analytics System

  • IIAS software overview
  • IIAS hardware overview
  • IIAS technologies overview
  • IIAS architecture overview

 

Unit 2: Introduction to Watson Studio on IBM Integrated Analytics System

  • Explore the community
  • Identify the role of projects
  • Identify analytic assets
  • Identify environments
  • Identify jobs
  • Identify collaborators

 

Unit 3: Work with notebooks

  • Work with notebooks
  • Load data into a notebook
  • Build a model
  • Save a model
  • Deploy a model

 

Unit 4: Work with R and RStudio

  • Describe the RStudio component of IBM Integrated Analytics System
  • Describe the data science capabilities of the RStudio component
  • Use RStudio to create and deploy a model

 

Unit 5: Optimize performance

  • In-database analytics versus in-application analytics
  • Explore in-database analytics using R and Python
  • Identify analytic stored procedures

 

Audience

Data scientists, data miners, statisticians, researchers, business analysts performing statistical modeling

Prerequisites

  • Familiarity with basic concepts in data science (machine learning models, scoring, deployment)
  • Basic knowledge of notebooks
  • Basic knowledge of Python and/or R

Content

Unit 1: Introduction to IBM Integrated Analytics System

  • IIAS software overview
  • IIAS hardware overview
  • IIAS technologies overview
  • IIAS architecture overview

 

Unit 2: Introduction to Watson Studio on IBM Integrated Analytics System

  • Explore the community
  • Identify the role of projects
  • Identify analytic assets
  • Identify environments
  • Identify jobs
  • Identify collaborators

 

Unit 3: Work with notebooks

  • Work with notebooks
  • Load data into a notebook
  • Build a model
  • Save a model
  • Deploy a model

 

Unit 4: Work with R and RStudio

  • Describe the RStudio component of IBM Integrated Analytics System
  • Describe the data science capabilities of the RStudio component
  • Use RStudio to create and deploy a model

 

Unit 5: Optimize performance

  • In-database analytics versus in-application analytics
  • Explore in-database analytics using R and Python
  • Identify analytic stored procedures

 


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