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Introduction to Data Mining and Predictive Analytics with RapidMiner

RapidMiner

Tuesday, April 23, 2013 at 8:30 AM - Wednesday, April 24, 2013 at 5:00 PM (PDT)

Introduction to Data Mining and Predictive Analytics wi...

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Event Details

Introduction to Data Mining and Predictive Analytics with RapidMiner

 

Tuesday, April 23rd and Wednesday, April 24th from 8:30 am to 5 pm

A light breakfast, lunch and afternoon snacks will be provided. A special dinner will be hosted by Rapid-I for all students on the Tuesday night.


Be sure to check out our Advanced Text and Web Mining Techniques with RapidMiner and RapidAnalytics course being held in the same location April 25 & 26.  Register for both at the same time to get a special discount.


Class size for this event is limited to 12 students.  If the class is sold out and you wish to be added to a waiting list, contact the event organizer.

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:

  • perform basic data preparations
  • build first predictive models,
  • evaluate the model’s quality
  • score new data sets


Details

  • Target audience: users, analysts, developers, administrators
  • 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

Neil McGuigan

Neil McGuigan is a Business Intelligence instructor at the Sauder School of Business at the University of British Columbia. Neil teaches in the MBA program, and has also taught seminars in Data Mining in the Master of Operations Research and Master of Journalism schools.

 

Mr. McGuigan has twelve years of experience in software development and management in the telecommunications and transportation industries. He served as the Chief Operating Officer of SJ Labs (now part of magicJack LP), where he managed large telecom data mining projects. He is currently the Chief Software Architect for a multi-national automotive software company.


Training Facility Logistics

The training will be held in downtown Vancouver at the CTC TrainCanada/MicroTek facilty.  The facility is near Vacouver's SkyTrain, SeaBus  and other public transportation.  Check their website for directions, nearby hotel and other information.

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Classes require a minimum of 3 students by April 15 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. 

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Can't make it? Sign up for our newletter at http://rapid-i.com/content/blogsection/5/66/lang,en/ (upper left corner) to stay in the loop on future events and classes.

 

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 April15.  No refunds will be given after this timeframe.

Have questions about Introduction to Data Mining and Predictive Analytics with RapidMiner? Contact RapidMiner

When & Where


CTC TrainCanada/MicroTek - Vancouver, BC
1155 West Pender Street
#650
Vancouver, BC V6E 2V2
Canada

Tuesday, April 23, 2013 at 8:30 AM - Wednesday, April 24, 2013 at 5:00 PM (PDT)


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Organizer

RapidMiner

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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