Subscribe to DSC Newsletter

US Training Courses for Open Source Data Mining Software RapidMiner (October 2008)

US Training Courses for Open Source Data Mining Software RapidMiner
New York & San Francisco, October 2008

Data Mining Training in New York:
http://rapid-i.com/content/view/106/125/

Data Mining Training in San Francisco:
http://rapid-i.com/content/view/105/121/

Open source software nowadays is a reliable and often more powerful alternative to closed source software. This is especially true in the case of software for data mining, text mining, web mining, predictive analytics, and business intelligence (BI). Open source based solutions in this field provide powerful functionality for a much lower price than proprietary products. As a consequence, freely available data mining and business intelligence solutions like RapidMiner [ www.RapidMiner.com ] are now among the most widely used solutions world-wide. According to the 2008 Data Mining Tool Poll by the leading data mining web portal KDnuggets, RapidMiner is the leading open source data mining software. Rapid-I [ www.rapid-i.com ], the company providing the open source data mining software RapidMiner, is a provider of predictive analytics, data mining, text mining, web mining, and sentiment analysis solutions and services and now offers the following one-day data mining training courses in New York and San Francisco on data mining in general, on data mining for customer relationship management, sales, and marketing, on advanced data mining methods, on data mining for time series predictions, on data mining for financial forecasting, on text mining, on web mining and sentiment analysis, and on data mining for developers:


(1) Data Mining and Predictive Analytics: Methods and Applications
(New York, October 6th, 2008):

Compact introduction into the foundations of data mining including both background knowledge as well as many practical exercises. Topics include methods like Decision Trees, Rule Learning, and Neural Networks as well as basic pre-processing techniques and a discussion of the most important explorative analysis methods.

(2) Data Mining for Marketing and Sales Optimization
(New York, October 7th, 2008):

Using data mining to optimize marketing and sales. Customer data analysis leads to models describing the behaviour of your customers to better target your marketing activities. This course also describes the practical steps necessary to create such models with the software RapidMiner. Topics include up- and cross-selling, market basket analysis, product recommendations, personalization, and customer relationship management (CRM).

(3) Advanced Data Mining Techniques and Processes for Professionals
(New York, October 8th, 2008):

Covers the automatic optimization of parameters, the optimization of the process structure itself, extended possibilities for guided feature selection and feature construction, the collection of process statistics, extended control of inputs and outputs, the definition and usage of macros, loops in processes and other meta operations.

(4) Data Mining for Predictive Time Series Analysis and Forecasting
(New York, October 9th, 2008):

Compact introduction into the foundations of statistical learning for forecasting and prediction. The task is to find the most probable value of a series of measurements for future time points. Topics include necessary pre-processing steps for numerical data transformations, an introduction into statistical regression methods, neural networks, and support vector machines (SVM), and a discussion of validation methods in order to measure the goodness of the predictions. These methods are especially useful for numerical predictions from series data as they often occur in financial markets but also in production settings and many other applications.

(5) Data Mining in Finance and Financial Forecasting
(New York, October 10th, 2008):

Demonstrates how data mining can be employed in various tasks in the financial sector by banks, investment funds, hedge funds, insurance companies, other financial institutions and companies in the finance sector as well as sophisticated private investors and traders. Financial data often comes in the form of time serieses, e.g. stock market prices, commodity prices, utility prices, or currency exchange rates observed over time. Data mining techniques can be used to analyze financial time series data, to find patterns, to detect anomalies and outliers, to recognize situations of chance and risk, to detect temporal changes in the correlation patterns and structures, to predict future demand, prices, and rates, to determine the most successful indicators, and to optimally combine such indicators to achieve strong predictive power.


(6) Data Mining and Predictive Analytics: Methods and Applications
(San Francisco, October 20th, 2008):

Compact introduction into the foundations of data mining including both background knowledge as well as many practical exercises. Topics include methods like Decision Trees, Rule Learning, and Neural Networks as well as basic pre-processing techniques and a discussion of the most important explorative analysis methods.

(7) Data Mining for Marketing and Sales Optimization
(San Francisco, October 21st, 2008):

Using data mining to optimize marketing and sales. Customer data analysis leads to models describing the behaviour of your customers to better target your marketing activities. This course also describes the practical steps necessary to create such models with the software RapidMiner. Topics include up- and cross-selling, market basket analysis, product recommendations, personalization, and customer relationship management (CRM).

(8) Text Mining: Advanced Pre-Processing, Classification, and Clusterin...
(San Francisco, October 22nd, 2008):

Introduction into knowledge discovery from unstructured data like text documents. It focuses on the necessary pre-processing steps and the most successful methods for automatic text classification (including Naive Bayes and Support Vector Machines, SVM) and text clustering. Many practical exercises for different settings (for example e-mail spam detection, automated e-mail routing, adaptive personal news filtering, etc.) will enable the participants to transfer the gained knowledge to own text mining problems.

(9) Web Mining: Analysing Web Usage, Extracting Information from Web So...
(San Francisco, October 23rd, 2008):

Shows how you could know what your customers and potential customers think about your products in a very timely and affordable fashion from information provided by them freely available in the web. This course enables you to quickly build mash-ups to extract and integrate information from various sources on the web and to automatically crawl and categorize web pages using the latest text mining technologies.

(10) Advanced Data Mining for Developers: Customizing and Extending Rapi...
(San Francisco, October 24th, 2008):

Aims at software developers and analysts with background knowledge in development. Gives a step-by-step introduction showing how new methods and operators can be integrated into the data mining solution RapidMiner. The second part of this course deals with the integration of RapidMiner into other software products as a data mining engine. This allows, for example, the application of learned models with one simple click for non-analysts or the addition of adaptive behavior to your products. All necessary steps will be discussed at hand of a simple but complete integration example.



Further information:

Data Mining Training in New York:
http://rapid-i.com/content/view/106/125/

Data Mining Training in San Francisco:
http://rapid-i.com/content/view/105/121/



About the Trainer of these Courses:

These training courses in New York and San Francisco will be given by Ralf Klinkenberg, initiator of the open source project RapidMiner (formerly YALE) and co-founder of Rapid-I, the company behind the project. Ralf Klinkenberg has more than 15 years of experience in data mining, text mining, web mining, sentiment analysis, machine learning, and related fields and has consulted many companies on how to best leverage these technologies for automating and/or optimizing their business.



About RapidMiner:

RapidMiner [ www.RapidMiner.com ] is the leading open source data mining software. According to a poll of the most important web portal for data mining and knowledge discovery, KDnuggets.com, in May 2008 among 347 data mining experts, RapidMiner is the most widely used open source data mining tool, the second most frequently employed software for data analysis overall. RapidMiner has thousands of users in more than 40 countries world-wide. During the last three years, RapidMiner was downloaded more than 300,000 times. RapidMiner provides more than 500 different modules for detecting patterns in data and for their 2D and 3D visualisation. RapidMiner supports data import from common data formats of other data mining tools, Excel sheets, SPSS files, all common databases, and unstructured text documents like news texts, e-mail messages, web pages, web blogs, PDF documents, as well as time series and audio data.



About Rapid-I:

Rapid-I [ www.rapid-i.com ] is a provider of predictive analytics, data mining, and text mining software, solutions, and services offering its customers automatable intelligent data analysis of large amounts of data and text including automatically generated classification and forecasting systems. The open-source data mining specialist Rapid-I enables other companies to use the latest technology for intelligent data analysis and for the discovery of still unused company knowledge from existing data. Rapid-I won the highly rewarded Open Source Business Award 2008. Rapid-I has a broad user and customer base in more than 40 countries world-wide including top companies like Ford, Honda, Nokia, Miele, Philips, IBM, HP, Cisco, Merrill Lynch, BNP Paribas, Bank of America, mobilkom austria, Akzo Nobel, Aureus Pharma, PharmaDM, Cyprotex, Celera, Revere, LexisNexis, and Mitre as well as many small and mid-sized companies. Rapid-I is headquartered in Dortmund, Germany. Besides of its since 2001 continuously improved data mining software RapidMiner, Rapid-I offers its customers a broad range of services including consulting, training, professional support, software development, RapidMiner customization and extensions as well as complete data analysis services from a single source. Further information is available at www.rapid-i.com .



References and Links:

http://www.ovum.com/news/euronews.asp?id=7137
Ovum Analyst Report: "German Rapid-I pushes open source data mining forward" (London, UK, June 2008).

http://rapid-i.com/content/view/99/66/
Rapid-I wins the Open Source Business Award 2008, the most highly rewarded European start-up prize.

http://www.imittelstand.de/auszeichnungen/innovationspreis2008/kate...
Within its "Innovation Award 2008", the German initiative for small and mid-sized businesses ("Innitiative Mittelstand") awarded RapidMiner as one of the most innovative open source solutions.

http://rapid-i.com/content/view/65/74/
KDnuggets Polls 2007 and 2008: RapidMiner is among the top 3 data mining tools worldwide and the leading open source data mining software.

http://rapid-i.com/content/view/8/56/
Selected customers of Rapid-I and users of RapidMiner:
* Market Research: GfK, Schober Information Group, AFO Marketing, maanto;
* Automobile: Ford, Honda;
* Manufacturing & Production Industry: Schott, ThyssenKrupp Nirosta, Salzgitter Mannesmann, AMS Engineering;
* Elektronics: Nokia, Philips, Miele;
* IT Sector: IBM, Cisco, HP, HP Labs, HRL Laboratories, TNO, BBN Technologies, LexisNexis, Mitre, General Dynamics Advanced Information Systems;
* Pharma, BioTech, Chemical Industry: Akzo Nobel, Aureus Pharma, Celera, Cyprotex, Elexso, PharmaDM, Revere, and Sanofi-Aventis, Europe's leading pharma company;
* Telecom Sector: mobilkom austria, Austria's leading mobile phone service provider;
* Utilities: E.ON Ruhrgas;
* Financial Sector and Insurance Companies:
* comdirect, a leading German online bank and broker,
* BNP Paribas, leading bank of France and Europe,
* Bank of America, second largest bank of the USA,
* Merrill Lynch, US investement bank,
* aiinvesting.com, US consultancy and hedge fund,
* NeuralMarketTrends.com, US consultancy and trader,
* Ineas, French insurance company,
* PentaSecurity, Chilenian insurance company,
* Allianz, Europe's leading insurance company.

http://rapid-i.com/content/view/7/95/
Current data mining and RapidMiner courses (detailed course schedules by clicking on course titles)

Tags: Analysis, Analytics, Business, Courses, Data, Financial, Forecasting, Francisco, Intelligence, Mining, More…New, Open, Opinion, Predictive, Rapid-I, RapidMiner, San, Seminar, Sentiment, Series, Software, Source, Text, Time, Training, USA, Web, Workshop, York

Views: 31

Attachments:

On Data Science Central

© 2019   AnalyticBridge.com is a subsidiary and dedicated channel of Data Science Central LLC   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service