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This training course is a compact two day introduction into the foundations of data mining and business analytics as well as into the software RapidMiner. After this training course the participants will have a complete understanding of how Rapid-I software works and is used. The overall data mining process is covered as well as the foundations of the software. Participants will be able to create predictive models in standard data environments typically found within most analyst positions. Due to a high number of practical exercises, the participants will be able to transfer the gained knowledge to own data mining problems and solve them quickly and easily.
After the training course the participants will have the ability to:
Previous knowledge: basic knowledge of computer programs and mathematics
Methods: lectures, discussions, individual and group work, exercises on realistic data.
Participants may introduce their own work and project specific questions in order to find particular solutions together with the trainer and other participants. The training course addresses beginners and intermediate learners.
Topics
Basic Usage
User Interface
Creating and handling RapidMiner repositories
Starting a new RapidMiner project
Operators and processes
Loading data from flat files
Loading data from databases
Storing data, processes and results
Data Preparation
Normalization and standardization
Basic transformations of value types
Handling missing values
Sampling
Filtering examples and attributes
Handling attribute roles
Predictive Models
Explorative data analysis including data visualization
Correlations
Linear Regression
Naïve Bayes
Decision Trees
Rules
Importance of attributes
Model Evaluation
Splitting data
Evaluation methods
Performance criteria
Lift charts
ROC plots
Scoring
Applying models
Prerequisites
You must bring a laptop to class (Windows, Mac or Linux OS is fine). Should have Java Runtime Environment (JRE) version 1.6 (officially Java 6.0) or later installed. Students will be provided with links to install the Community Version of RapidMiner prior to the class.
Instructor
David Weisman
David Weisman is a data scientist consultant with over 35 years of experience in the software field. In addition to consulting, he is a researcher at the University of Massachusetts Boston, working at the intersection of molecular biology and data mining. David is searching for cancer biomarkers in enormous volumes of DNA sequence data, identifying biosensors of environmental pollutants in bacterial and plant transcriptomic data, and teaching bioinformatics courses. Prior to obtaining his recent Ph.D. in molecular biology, David ran a long-term successful software consulting firm, specializing in distributed system development, compiler design, operating system development, quantitative finance, network security, and health care informatics.
Training Facility Logistics
The training will be held in downtown Boston at the MicroTek/Compuworks training facility. The facility is near Boston's South Station and other public transportation. Check their website for directions, specials on parking and nearby hotels (use their name and you should get the corporate rate).
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Classes require a minimum of 3 students by June 11 to be held. If there are insufficient registrants, the class may be cancelled and all students will be refunded the full registration fee. Students should organize their travel arrangements accordingly and with this proviso. Rapid-I will promptly notify registered users as soon as the 3 students quota will be met.
Our Refund Policy: Plans change? We get it. But if you can't make it to the class, please email us at training@rapid-i.com no later than June 10. No refunds will be given after this timeframe.
Have questions about Introduction to Data Mining and Predictive Analytics with RapidMiner?
Contact RapidMiner
When & Where
MicroTek/CompuWorks – Boston, MA
263 Summer Street
Boston,
MA 02210
Tuesday, June 18, 2013 at 8:30 AM - Wednesday, June 19, 2013 at 5:00 PM (EDT)
RapidMiner builds software for real data science, fast and simple. We make data science teams more productive through a lightning fast platform that unifies data prep, machine learning, and predictive model deployment. More than 250,000 users in over 150 countries use RapidMiner products to drive revenue, reduce costs, and avoid risks.
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