IBM Integrated Analytics System (IIAS) for Data Scientists (V1.0) eLearning – 1W710G WBT
Details
Course Code: 1W710G
Brand: HDM – IBM Integrated Analytics Systems
Category: Analytics
Skill Level: Intermediate
Duration: 5.0H
Modality: WBT
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
Short Summary
This course teaches data scientists how to use the data science capabilities of IBM Integrated Analytics System.
Overview
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.
Topic
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
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
