When does class start/end?
Classes begin promptly at 9:00 am, and typically end at 5:00 pm.
This IBM Web-Based Training (WBT) is Self-Paced and includes: - Instructional content available online for duration of course - Visuals without hands-on lab exercises This course teaches data...
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This IBM Web-Based Training (WBT) is Self-Paced and includes:
- Instructional content available online for duration of course
- Visuals without hands-on lab exercises
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 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
Data scientists, data miners, statisticians, researchers, business analysts performing statistical modeling
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