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94% of in-person attendees rated the course Excellent or Very Good ( details) What is predictive analytics?
Predictive analytics is business intelligence technology that produces
a predictive score for each customer or prospect. Each customer's
predictive score informs actions to be taken with that customer —
business intelligence just doesn't get more actionable than that.
Predictive Analytics Applied is a self-paced online course that covers the following topics:
- Applications: Business, marketing and web problems solved with predictive analytics
- Core technology: How a predictive model works and how it's created
- Evaluation: How well a predictive model works and how much revenue it generates
- Management: Project leadership and business process for predictive analytics
- Illustrations: Live demos and detailed case studies
- Hands-on: "Get your hands dirty" with a
revealing Excel-based exercise, bringing a predictive model to life and seeing it improve before your eyes
View a free 13-minute overview
video of this online training program, and access a detailed
outline of its four training modules and a complete summary of course
"take-aways".
Online course content and format:
Predictive Analytics Applied covers 40% of the material of Prediction Impact's
in-person seminar with four jam-packed training modules of 60-90
minutes each, totaling 5 1/2 hours of viewing time. Since no travel
is required and the registration fee is one-third the fee of the
in-person training, it provides an economical alternative for ramping
up on predictive analytics.
Online training participants receive:
Online video format. This online training program consists of
high-quality videos recorded for online viewing (not the recording of
a live seminar). The videos consist of training content, software
demos and intermittent instructor appearances, with verbal instruction
throughout. The video image is large - the resolution
is 800 by 600 (960 by 655 including video control areas), which is a
large portion of your screen - possibly the entirety of your screen,
depending on its resolution.
Each of the four training modules of this self-paced e-learning
program may be viewed at your convenience, pausing, rewinding and
fast-forwarding as needed. Since the contents are concentrated, the
recommended pace is to view one module per week. On the faster side,
the entire program may be "crammed" in just four days by viewing one
60-to-90 minute module per day.
Online training vs. the in-person seminar
Not sure where to start? Make use of our follow-on discount
for the in-person training: Online training participants may
subsequently apply half their registration fee towards registration
for Prediction Impact's 2-day
in-person seminar on predictive analytics. This option holds
for 18 months after participating in the online training.
This way, online participants can later reap the benefits of the
extensive in-person training program — gaining valuable
reinforcement of the concepts and networking with colleagues —
at a discounted rate. The in-person training program covers over twice
the content and examples of the online program,
including additional detailed case studies and demos, more extensive
coverage of core predictive modeling methodology, and breakout
problem-solving sessions with colleagues. Read the in-person course
description for more information.
Who this online course is for:
Managers. Project leaders, directors, CXOs, vice presidents, investors and decision makers of any kind involved with analytics, direct marketing or online marketing activities.
Marketers. Personnel running or supporting direct marketing, response modeling, or online marketing who wish to improve response rates and increase campaign ROI for retention, upsell and cross-sell.
Technology experts. Analysts, BI directors, developers, DBAs, data warehousers, web analysts, and consultants who wish to extend their expertise to predictive analytics.
In order to meet the unique training needs of business decision makers and analytics practitioners, this training program is:
- Business-focused. Unlike other training programs that also cover scientific, engineering and medical applications of data mining and analytics, this seminar focuses squarely on solving business and marketing problems with these methods.
- Comprehensive across business needs. Within this realm, however, we step beyond the standard application of response modeling for direct marketing to solve a wide range of business problems.
- Vendor-neutral and method-neutral. This training program, which is not run by an analytics software vendor, provides a balanced view across analytics tools and methods.
No background in statistics or modeling is required. The only specific knowledge assumed for this training program is moderate experience with Microsoft Excel or equivalent.
Please contact Prediction Impact with any questions about this training program.
Start learning right now
The following short, published articles, written by the instructor, are a great place to get started. Note that these articles are not required reading; most of the material therein will be covered during the training program.
Predictive Analytics with Data Mining: How It Works
Get a handle on the functional value of predictive analytics for marketing, sales and product direction.
DM Review's DM Direct
Driven with Business Expertise, Analytics Produces Actionable Predictions
Run data mining as a business activity to generate customer predictions that will have a business impact. CRM Magazine's DestinationCRM.
Predictive Analytics' Killer App: Retaining New Customers
Predictively targeted discounts convert new customers who would otherwise never return to become loyal customers. DM Review's Extended Edition.
About the instructor
 Eric Siegel, Ph.D., is a seasoned consultant in data mining and analytics, an acclaimed industry instructor, and an award-winning teacher of graduate-level courses in these areas. Eric served as a computer science professor at Columbia University, where he developed data mining technology in the realms of machine learning performance optimization, integrating historical databases, text mining, and data visualization. The chair of the Predictive Analytics World Conference, Eric has authored 11 peer-reviewed research publications and ran an MIT-hosted symposium on data mining. He also co-founded two New York City-based software companies for customer/user profiling and data mining. With data mining, Eric has solved problems in CRM analytics, computer security, fraud detection, text mining and information retrieval.
Eric has taught industry programs through Prediction Impact, The Modeling Agency and Salford Systems. In addition, he taught many semesters of university courses, including data mining-related graduate courses as well as introductory lecture series for non-technical audiences. Two of these courses have been in syndication through the Columbia University Video Network. Eric also published three peer-reviewed papers on computer science education.
Register for immediate access
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