Data Mining: SAS Enterprise Miner Practicum

Brief Description:

The purpose of this course is to take the knowledge learned in Introduction to Data Mining and Data Mining: Unsupervised Techniques and apply it using SAS Enterprise Miner.

Instructor(s):
Level: Intermediate

Who Should Take This Course:

Analysts who are familiar with the data mining concepts, and who need to acquire facility and (optionally) statistics.com certification in using SAS Enterprise Miner.

Dates:
To be scheduled.
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Registration:
Please read the syllabus tab, noting the prerequisites, text and software requirements.

Register Online -$399
Register Online -$299 (you must be affiliated with a college, university or high school)

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Data Mining: SAS Enterprise Miner Practicum

Aim of Course:

The purpose of this course is to take the knowledge learned in Introduction to Data Mining and Data Mining: Unsupervised Techniques and apply it using SAS Enterprise Miner. There will be practical exercises in prediction and classification using neural nets, classification and regression trees, logistic regression, Naive Bayes, and k-nearest neighbor. There will also be exercises in unsupervised methods: clustering, principal components and association rules.

This course is a core requirement or elective in the following Program(s) in Analytics and Statistical Studies (PASS):

• Data Mining

Prerequisite(s):
Introduction to Predictive Modeling course and Data Mining: Unsupervised Techniques are both prerequisites for this course.
Course Program:

SESSION 1: Introduction to CRM Modeling and SAS Enterprise Miner

SESSION 2: Classification for Retention with Logistic Regression and Ensembles

SESSION 3: Behavioral Modeling with Temporal Abstractions

SESSION 4: Credit Risk Modeling and Credit Scoring

 

Students will use SAS Enterprise Miner (SAS-EM) with data sets and exercises to reinforce and assess the material learned in our Introduction to Data Mining course and Data Mining: Unsupervised Techniques (classification, prediction, model choice and evaluation, clustering, PCA, association rules).

Organization of the Course:

This course takes place over the internet at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

The course typically requires 15 hours per week. At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Credit:
Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:

1. You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
2. You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
3. You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course, 5.0 CEU's and a record of course completion will be issued by The Institute, upon request.

Course Text:

The text is Handbook of Statistical Analysis and Data Mining Applications by Robert Nisbet, John Elder, and Gary Miner, published by Elsevier and available here.

Software:

A special edition of SAS Enterprise Miner will be made available to students when they purchase the course text.

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Yes, I want to register for:

Data Mining: SAS Enterprise Miner Practicum

Instructor(s):
Dates:
To be scheduled.
Course Fee: $399
Academic Rate: $299

Before registering, please read the syllabus tab, noting the prerequisites, text and software requirements. When you click the register button, you will be taken to our secure transaction page.

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