Data Mining PASS
This certificate program is for those who want to learn data mining methods (including predictive analytics). It offers the equivalent of 18 credits (in the US academic system).
This program provides an appropriate balance between conceptual understanding and application. As a successful PASS candidate, you will acquire the statistical skills and software facility you need for projects, reports, and research. While open to all, the flexible format and scheduling is particularly suitable for working professionals.
The program courses are taught by leading experts with whom you share a private discussion forum for the entire course period. Students participate from all over the world - lessons and assignments are opened and closed on a weekly basis. You organize your time however you like within each week - there are no set times when you must be online.
Courses in the Program are typically 4 weeks long, and require about 15 hours per week. Courses operate throughout the year, and there is no "semester" system. You can enter and start taking courses whenever you like, after reviewing the Program requirements and guidance on course sequencing. Most students take one course at a time, and complete their Program over a period of 3-5 years.
There are four main components to each course:
- Course materials (course text, course files, video and other materials)
- Discussion with the instructor and other students via daily web forum (asynchronous - you need not be online at any particular time of day)
- Homework (submitted online weekly, with individualized feedback the following week)
- Final project/exam
For more details on how these online courses work, click here. Students successfully completing the Program receive a certificate and transcript.
Placement Services
As a PASS candidate, once you successfully complete half your program courses, you are eligible for our personalized placement services. We will review your background, your interests, and your work at the Institute, and try to find a match with appropriate recruiters. Our specialty is early-to-mid-career placement (not entry level).
When To Apply
Applications are accepted and students are enrolled year round on a rolling basis. You pay an application fee and submit it with your application form. You may pay the fee online here, or enclose a check (USD drawn on a US bank) with your application. NOTE: The application is your opportunity to specifically outline your past education and experience, and provide any other information you want us to consider during our review. The value of this background and experience is the ability to place the statistical methods covered in the Program in an appropriate application context. Once we have accepted your application, we will be happy to assist you with more specific questions about PASS.
Admission Criteria
- A Bachelor's degree from an accredited college or university,
- Successful completion of an introductory statistics course equivalent to Statistics.com's Intro courses series ("Introduction to Statistics for Beginners" through "Introduction to Statistics 3") that prepares the applicant for a passing score in the required entrance exam which covers basic statistics.
- Passing score on the online entrance exam.
Note: While it is not an admission requirement, applicants will also benefit from employment experience (or plans for employment) in an organization that works in the selected field of the Program you select.
Enrollment In PASS
Enroll in the Program of your choice here, after your application is approved AND you have passed the entrance examination. Once enrolled, register for each specific course within your PASS using the academic tuition rate as you are now a matriculated student at the Institute for Statistics Education at Statistics.com.
Note: While it is not an admission requirement, applicants will also benefit from employment experience (or plans for employment) in an organization where quantitative analysis informs business practice and decision-making. The value of this experience is the ability to place the statistical methods covered in the Program in an appropriate business context (work experience with particular statistical techniques is not required).
Application Fee: $75
Program Registration Fee:$495
Estimated Required Course Tuition: $2394
Estimated Electives Course Tuition: $2231
Estimated Material Cost: $840
Estimated Total Cost: $6035
Data Mining PASS
Program Objective
The program consists of courses offered completely online at statistics.com, accessible via any computer connected to the internet. Required topics for all students include supervised learning (a technical term referring to statistical and machine learning methods for developing predictive models based on data with known outcomes), and unsupervised learning (customer segmentation, recommender systems). Electives allow for in-depth study of advanced data mining techniques such as support vector machines, natural language processing or sentiment analysis, as well as a variety of related statistical methods. Students completing the Program successfully will gain mastery of conceptual skills and software applications in data mining (including predictive analytics).
Sequencing your Program
Most courses are four weeks long, and are scheduled either once or twice a year. Courses start on specific dates, but do not require you to be online at any particular time of the day. Since various courses are available throughout the year, the Program provides flexibility in scheduling.
Listed below in alphabetical order, are the required and elective courses with available dates. Additionally, use these tools to help you map out your program:
- Prerequisites – each course lists its prerequisite. These prerequisite courses should be taken prior to the course you are considering.
- Suggested sequencing document - this lists the courses in groups, based upon their approximate level of difficulty. It is a guide, not a set of requirements.
- Calendar - You can easily search course start dates here.
After your successful acceptance into PASS, you can begin your program with any course, based on your own background, the level of difficulty and if you meet the prerequisites. You will work out a tentative schedule (or at least the first few courses), then register and pay tuition.
As a PASS candidate, you are eligible to register for any course using the academic tuition link, indicating “PASS” when prompted for your academic affiliation during online registration. As an added benefit, if you register online for three courses simultaneously, an automatic USD200 reduction is applied. Please note that payment of tuition and fees does not include the purchase of any required texts or software.
Suggested sequencing document
Calendar
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Required Courses (6)
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Data Mining: Unsupervised Techniques
This course covers key unsupervised learning techniques - association rules, principal components analysis, and clustering. The course will include an integration of supervised and unsupervised learning techniques.
Tuition: $399 (5.0 CEUs)
New available dates:
October 12, 2012 to November 09, 2012October 11, 2013 to November 08, 2013 more >>
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Interactive Data Visualization
This course covers the principles of the visual display of data, both for presentation and analysis.
Tuition: $399 (5.0 CEUs)
New available dates:
April 27, 2012 to May 25, 2012October 26, 2012 to November 23, 2012 more >>
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Introduction to Data Mining
This course covers the two core paradigms that account for most business applications of data mining: classification and prediction. The course includes hands-on work with XLMiner, a data-mining add-in for Excel.
Tuition: $399 (5.0 CEUs)
New available dates:
March 09, 2012 to April 06, 2012September 07, 2012 to October 05, 2012 more >>
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Logistic Regression
Logistic regression extends ordinary least squares (OLS) methods to model data with binary (yes/no, success/failure) outcomes. Rather than directly estimating the value of the outcome, logistic regression allows you to estimate the probability of a success or failure.
Tuition: $399 (5.0 CEUs)
New available dates:
March 16, 2012 to April 13, 2012June 15, 2012 to July 13, 2012September 07, 2012 to October 05, 2012 more >>
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Matrix Algebra Review
This course will provide the basics of vector and matrix algebra and operations necessary to understand multivariate statistical methods, including the notions of the matrix inverse, generalized inverse and eigenvalues and eigenvectors. After successfully completing this course, you will be able to use and understand vector and matrix operations and equations, find and use a matrix inverse, and use and understand the eigenset of a symmetric matrix.
Tuition: $399 (5.0 CEUs)
New available dates:
February 24, 2012 to March 23, 2012June 29, 2012 to July 27, 2012November 02, 2012 to November 30, 2012 more >>
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Regression Analysis
In this course you will learn how multiple linear regression models are derived, use software to implement them, learn what assumptions underlie the models, learn how to test whether your data meet those assumptions and what can be done when those assumptions are not met, and develop strategies for building and understanding useful models.
Tuition: $399 (5.0 CEUs)
New available dates:
March 30, 2012 to April 27, 2012September 28, 2012 to October 26, 2012 more >>
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Elective Courses (6 required)
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Cluster Analysis
This course will teach you how to use various cluster analysis methods to identify possible clusters in multivariate data. Methods discussed include hierarchical clustering, k-means clustering, two-step clustering, and normal mixture models for continuous variables.
Tuition: $399 (5.0 CEUs)
New available dates:
November 02, 2012 to November 30, 2012November 01, 2013 to November 29, 2013 more >>
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Data Mining - R
The main goal of this course is to teach users how to perform data mining tasks using R.
Tuition: $399 (5.0 CEUs)
New available dates:
June 29, 2012 to July 27, 2012 more >>
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Data Mining - STATISTICA Data Miner Practicum
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 STATISTICA Data Miner, focusing on the automated and semi-automated modeling features of the package.
Tuition: $399 (5.0 CEUs)
New available dates:
To be scheduled. more >>
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Data Mining Mistakes and How to Avoid Them
The very nature of data mining makes it prone to error. This course reviews and illustrates the typical sources of error, and how to avoid them.
Tuition: $179 (5.0 CEUs)
New available dates:
October 12, 2012 to October 26, 2012 more >>
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Data Mining: SAS Enterprise Miner Practicum
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.
Tuition: $299 (5.0 CEUs)
New available dates:
To be scheduled. more >>
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Decision Trees and Rule-Based Segmentation
Rule induction is an important component of data mining, and this course covers two main styles of generating rules.
Tuition: $399 (5.0 CEUs)
New available dates:
January 18, 2013 to February 15, 2013 more >>
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Introduction to Support Vector Machines in R
This course begins by developing basic concepts such as hyperplanes, features spaces and kernels; then it covers the development of support vector machines (SVM's).
Tuition: $399 (5.0 CEUs)
New available dates:
November 16, 2012 to December 14, 2012 more >>
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Missing Data Analysis in Clinical Trials
This course will cover the theory and practice of two modern methods of handling missing data in clinical trial applications: maximum likelihood and multiple imputation.
Tuition: $399 (5.0 CEUs)
New available dates:
To be scheduled. more >>
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Natural Language Processing
This course is designed to give you an introduction to the algorithms, techniques and software used in natural language processing (NLP).
Tuition: $399 (5.0 CEUs)
New available dates:
August 31, 2012 to September 28, 2012August 30, 2013 to September 27, 2013 more >>
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Sentiment Analysis
Sentiment Analysis refers to the process of identifying, extracting and classifying opinions in text segments. With the rise of social media and the ability of end-users to express and share their personal views easily, the need to automatically gauge user-sentiment has become increasingly important for CRM, online advertising and brand analysis.
Tuition: $339 (3.75 CEUs)
New available dates:
July 20, 2012 to August 10, 2012July 19, 2013 to August 09, 2013 more >>
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Spatial Analysis Techniques in R
This course will teach users how to implement spatial statistical analysis procedures using R software.
Tuition: $399 (5.0 CEUs)
New available dates:
December 14, 2012 to January 18, 2013December 13, 2013 to January 17, 2014 more >>
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Spatial Statistics with Geographic Information Systems
Spatial statistical analysis uses methods adapted from conventional statistics to address problems in which spatial location is the most important explanatory variable. This course will explain and give examples of the analysis that can be conducted in a geographic information system such as ArcGIS or Mapinfo.
Tuition: $399 (5.0 CEUs)
New available dates:
May 11, 2012 to June 08, 2012November 09, 2012 to December 07, 2012 more >>
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Statistical Analysis of Microarray Data with R
This course will acquaint you with the process of analysis of microarray data. You will learn how to preprocess the data, short list the differentially expressed genes, carryout principal component analysis to reduce the dimensionality and to detect interesting gene expression patterns, and clustering of genes and samples. Illustrations of the statistical issues involved at the various stages of the analysis will use real data sets from DNA microarray experiments.
Tuition: $399 (5.0 CEUs)
New available dates:
April 20, 2012 to May 18, 2012October 19, 2012 to November 16, 2012 more >>
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Text Mining
This course will introduce the essential techniques of text mining, understood here as the extension of data mining's standard predictive methods to unstructured text.
Tuition: $399 (5.0 CEUs)
New available dates:
June 08, 2012 to July 06, 2012 more >>
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Download Application
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Click Here.