Predictive Analytics Preview

Predictive Analytics - a 1 week preview

 

Aim of Course:

In this 1 week preview of “Predictive Analytics 1 - Machine Learning Tools,” you will be introduced to the basic concepts in predictive analytics, also called predictive modeling, the most prevalent form of data mining.

The session is also intended as a preview and illustration of how courses operate at The Institute for Statistics Education. 

FREE: Our 1-week preview covers how to fit and assess the performance of predictive models with multiple linear regression and k-nearest-neighbors, including use of holdout data. Sign up here and we will send details and a code for a full waiver of the $99 course fee.
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Course Program:

WEEK 1: Preparation, Classification and Prediction

  • What is supervised learning
  • Data partitioning and holdout samples
  • Choosing variables (features)
  • Handling missing data
  • Visualization and exploration
  • K-Nearest-Neighbors (KNN)
    • Measuring distance
    • Choosing k
    • Generating classifications and predictions
Homework:

Homework in this course consists of short answer problems, and includes exercises that require the use of computer software.

This course also has supplemental readings available online.

 


Predictive Analytics Preview

Who Should Take This Course:

Marketing and IT managers, financial analysts and risk managers, accountants, data analysts, data scientists, forecasters, and anyone considering taking a course at Statistics.com who wants to see how our courses operate. This course is especially useful if you want to understand what predictive modeling might do for your organization.

 

 

Level:
Introductory/Intermediate
Prerequisite:
You should be familiar with introductory statistics.  Try these self tests to check your knowledge.
Organization of the Course:

This course takes place online at the Institute for 1 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.

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.

Time Requirement:
About 15 hours per week, at times of  your choosing.

Options for Credit and Recognition:Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:
  1. No credit - You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. Certificate - 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. CEUs and/or proof of completion - 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,  CEU's and a record of course completion will be issued by The Institute, upon request.
  4. Other options - Statistics.com Specializations, INFORMS CAP recognition, and academic (college) credit are available for some Statistics.com courses

Course Text:
The required text for this course is Data Mining for Business Analytics: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner, 3rd Edition, by Shmueli, Patel and Bruce. Selections from this text will be provided in the one week session.
Software:

This 1 week preview is a hands-on session, and participants will apply data mining algorithms to real data.  The course is built around XLMiner, which is available:

  • For Windows versions of Excel, or
  • Over the web

Course participants will have access to a no-cost license for XLMiner.

Instructor(s):

Dates:

May 19, 2017 to May 26, 2017

Predictive Analytics Preview

Instructor(s):

Dates:
May 19, 2017 to May 26, 2017

Course Fee: $99

Do you meet course prerequisites? What about book & software? (Click here to learn more)

Group rates: Click here to get information on group rates. 

First time student or academic? Click here for an introductory offer on select courses. Academic affiliation?  You may be eligible for a discount at checkout.

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Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment. Please use this printed registration form, for these and other special orders.

Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise.

The Institute for Statistics Education is certified to operate by the State Council of Higher Education in Virginia (SCHEV).

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