Duration
14 hours (usually 2 days including breaks)
Requirements
- An understanding of data science concepts
Overview
RapidMiner is an open source data science software platform for rapid application prototyping and development. It includes an integrated environment for data preparation, machine learning, deep learning, text mining, and predictive analytics.
In this instructor-led, live training, participants will learn how to use RapidMiner Studio for data preparation, machine learning, and predictive model deployment.
By the end of this training, participants will be able to:
- Install and configure RapidMiner
- Prepare and visualize data with RapidMiner
- Validate machine learning models
- Mashup data and create predictive models
- Operationalize predictive analytics within a business process
- Troubleshoot and optimize RapidMiner
Audience
- Data scientists
- Engineers
- Developers
Format of the Course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- To request a customized training for this course, please contact us to arrange.
Course Outline
Introduction
Installing and Configuring RapidMiner
Overview of RapidMiner Studio Interface and Mechanics
Recap of the Analytical Cycle
Overview of Repository
Importing Data
Preparing Data
Modeling
Validation
Using Macros
Using Global Search
Buidling More Sophisticated Predictive Models
Evaluating Model Quality
Troubleshooting and Optimization
Summary and Conclusion