This 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.

Unit 1 Introduction to IBM Integrated Analytics System IIAS software overview IIAS hardware overview IIAS technologies overview IIAS architecture overviewUnit 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 collaboratorsUnit 3 Work with notebooks Work with notebooks Load data into a notebook Build a model Save a model Deploy a modelUnit 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 modelUnit 5 Optimize performance In-database analytics versus in-application analytics Explore in-database analytics using R and Python Identify analytic stored procedures

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

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

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