PREDICTIVE ANALYTICS FOR THE ENTERPRISE: MODEL DEVELOPMENT

ABOUT THIS COURSE

The Modeling Agency’s “Model Development” course presents a deep dive into the data mining process at a tactical level.  Attendees will observe demonstrations of machine learning methods and computer-guided analytical techniques for extracting and interpreting complex patterns and relationships from large volumes of data.  If you desire an intensive tactical orientation to data mining concepts, tools, techniques and supporting methods, then this event is designed for you.

This vendor-neutral course broadly covers data-driven information discovery techniques and model-building tactics without restriction to any particular modeling tool. Popular open-source and commercial packages are leveraged to illustrate methods, but not to showcase the tools. There are no prerequisites for this course.  However, participants will benefit by reviewing the CRISP-DM guide ahead of the training.

Each course in the series is designed to be taken independently or as a natural progression from tactics to strategy and practice.  View the course series overview page to compare the two primary orientations and target the most fitting agenda for your experience, situation and objectives.

WHO SHOULD ATTEND

IT PROFESSIONALS: who wish to expand their skills in this increasingly visible area within the corporate IT agenda

PROJECT LEADERS: who must report on developmental progress, resource requirements and system performance

DECISION SUPPORT SYSTEM ARCHITECTS: who require an understanding of the infrastructures required for supporting a data mining solution

BUSINESS ANALYSTS: who must develop and interpret the models, communicate the results and make actionable recommendations

FUNCTIONAL ANALYSTS: Customer Relationship Managers, Risk Analysts, Business Forecasters, Statistical Analysts, Inventory Flow Analysts, Direct Marketing Analysts, Medical Diagnostic Analysts, Market Timers, e-commerce System Architects and Web Data Analysts

BENEFITS OF ATTENDING

• Vendor-neutral exposure to tools and techniques that will place you months ahead in method planning and product surveying
• Examine which methods and tools are most effective for your needs
• Avoid pitfalls in data preparation, modeling, and results interpretation
• Leave with resources, contacts and actionable plans to substantially increase your analysis capabilities while minimizing dead ends

THE BUSINESS CHALLENGE

The rapid emergence of electronic data processing and collection methods has led some to call recent times as the “Information Age.”  However, it may be more accurately termed as “The Age of the Data Glut.”  Most businesses either posses a large database or have access to one.  These databases contain so much data that it becomes very difficult to understand just what that data is telling us.
There is hardly a transaction that does not generate a computer record somewhere.  All this data has meaning with respect to making better prospective business decisions  and anticipating customer needs and preferences.  But how do you discover those needs and preferences in a database that contains gigabits of seemingly incomprehensible numbers and facts?  Data mining and predictive analytics does just that.

The intent of this course is to offer attendees a stronger grasp of data mining techniques, a solid understanding of how various methods and tools apply to different kinds of data intensive problems, and how to overcome limitations that cause predictive models to underperform.

WHAT YOU WILL LEARN

• The data mining process and general implementation
• How to prepare raw data and benefit from visualization
• Various data mining methods and how they compare
• Advanced model building techniques
• Results analysis and validation
• Technology and product selection
• Solution integration, ongoing performance and maintenance
• Where to begin and how to obtain resources and support

WHAT MAKES THIS COURSE UNIQUE

This course does not restrict or skew the presentation of data mining methods through a single product.  Rather, the course gives consideration to all resources from a vendor-neutral position. The instructor possesses a wealth of pragmatic experience in applying data mining technology across industries in real-world applications.  This course insists upon making predictive analytics constructive and interpretable in a business or organizational setting.

In addition, live modeling demonstrations projected from the presenter’s machine will support the instructional sessions. The demonstrations will highlight superior performance as well as pitfalls. The instructor will show how to evaluate various packages based on strengths, limitations, value and general performance.