San Francisco, California
London, United Kingdom
Introduction to Data Mining and Predictive Analytics with RapidMiner
Tuesday, July 9th and Wednesday, July 10th from 8:30 am to 5 pm
A light breakfast, lunch and afternoon snacks will be provided.
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
- 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.
- 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
- Filtering examples and attributes
- Handling attribute roles
- Predictive Models
- Explorative data analysis including data visualization
- Linear Regression
- Naïve Bayes
- Decision Trees
- Importance of attributes
- Model Evaluation
- Splitting data
- Evaluation methods
- Performance criteria
- Lift charts
- ROC plots
- Applying models
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.
Bonnie K. Holub
Bonnie K. Holub, Ph.D. is the CEO of ArcLight, Inc., a small company that focuses on Data Analytics, Data Visualization, and Big Data. She founded it in late 2010 after she sold her ownership shares in Adventium. She also holds the Honeywell Endowed Chair in Global Technology Management in the Graduate Programs in Software, School of Engineering, University of St. Thomas, St. Paul, MN. She has held this chair since 2011. She teaches classes in eCommerce, Data Analytics and Visulization, and is a co-founder of the Center of Excellence for Big Data (CoE4BD). She tweets as bonnieholub.
Training Facility Logistics
The training will be held in downtown Boston at the Euler Training Center/MicroTek training facility. The facility is located 5 miles west of downtown Minneapolis, in the new West End area of St. Louis Park. Check their website for directions, parking and nearby hotels (use their name and you should get the corporate rate).
Classes require a minimum of 3 students by July 3 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.
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 firstname.lastname@example.org no later than July 2. No refunds will be given after this timeframe.
When & Where
RapidMiner offers a variety of ways to learn and develop your skills with the RapidMiner product suite. Our training courses are the most efficient and effective way for data analysts, data scientists, and administrators to get started with RapidMiner. They are also the perfect preparation for our , which can qualify you as a Certified RapidMiner Analyst and Certified RapidMiner Expert.