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Analytics for Data Science Certificate Program

Certificate Program Tuition and Fees
As a candidate, you are eligible for academic  tuition - type "PASS" when prompted for your academic affiliation during online registration to receive a reduced tuition per course.  If you register online for three courses, an automatic $200 reduction is applied.  

Please note that payment of the tuition does not include the purchase of any required texts or software. 

The total cost of the program varies depending on the electives chosen. Actual fees may differ from the estimate below. Fees are subject to change without prior notice.

Application Fee: $75
Program Registration Fee:$695
Estimated Required Course Tuition: $4002
Estimated Electives Course Tuition: $1623
Estimated Material Cost: $770
Estimated Total Cost: $7165

Analytics for Data Science Certificate Program

Program Content

The Analytics for Data Science Certificate Program consists of courses offered completely online at Statistics.com. There are required topics and a selection of electives.

Planning my 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.

Course ListExplore elective options, including suggested concentration strands

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FULL PROGRAM LIST

Required Courses (8)

  • Forecasting Analytics This course will teach you how to choose an appropriate time series model, fit the model, to conduct diagnostics, and use the model for forecasting. Tuition: $499 (5.0 CEUs) New available dates:
    September 12, 2014 to October 10, 2014March 27, 2015 to April 24, 2015July 31, 2015 to August 28, 2015November 27, 2015 to December 25, 2015March 25, 2016 to April 22, 2016July 29, 2016 to August 26, 2016November 25, 2016 to December 23, 2016March 24, 2017 to April 21, 2017July 28, 2017 to August 25, 2017November 24, 2017 to December 22, 2017March 23, 2018 to April 20, 2018July 27, 2018 to August 24, 2018November 23, 2018 to December 21, 2018
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  • Interactive Data Visualization This course covers the principles of the visual display of data, both for presentation and analysis. Tuition: $499 (5.0 CEUs) New available dates:
    October 31, 2014 to November 28, 2014February 13, 2015 to March 13, 2015June 12, 2015 to July 10, 2015October 30, 2015 to November 27, 2015February 12, 2016 to March 11, 2016June 10, 2016 to July 08, 2016October 28, 2016 to November 25, 2016February 10, 2017 to March 10, 2017June 09, 2017 to July 07, 2017October 27, 2017 to November 24, 2017February 09, 2018 to March 09, 2018June 08, 2018 to July 06, 2018October 26, 2018 to November 30, 2018
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  • Introduction to Optimization The course introduces the use of mathematical models for managerial decision making and covers how to formulate linear programming models for decision problems where multiple decisions need to be made in the best possible way while simultaneously satisfying a number of logical conditions (or constraints). You will learn how to use spreadsheet software to implement and solve these linear programming problems. Tuition: $549 (5.0 CEUs) New available dates:
    August 22, 2014 to September 19, 2014January 09, 2015 to February 06, 2015August 21, 2015 to September 18, 2015January 08, 2016 to February 05, 2016August 19, 2016 to September 16, 2016January 06, 2017 to February 03, 2017August 18, 2017 to September 15, 2017January 05, 2018 to February 02, 2018August 17, 2018 to September 14, 2018
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  • Introduction to Social Network Analysis (SNA) This course will teach a mix of quantitative and qualitative methods for describing, measuring and analyzing social networks. Tuition: $469 (5.0 CEUs) New available dates:
    August 15, 2014 to September 12, 2014February 27, 2015 to March 27, 2015August 14, 2015 to September 11, 2015February 26, 2016 to March 25, 2016August 12, 2016 to September 09, 2016February 24, 2017 to March 24, 2017August 11, 2017 to September 08, 2017February 23, 2018 to March 23, 2018August 10, 2018 to September 07, 2018
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  • Predictive Analytics 1 - Machine Learning Tools This course covers the two core paradigms that account for most business applications of predictive modeling: classification and prediction. The course includes hands-on work with XLMiner, a data-mining add-in for Excel. Tuition: $469 (5.0 CEUs) New available dates:
    October 24, 2014 to November 21, 2014January 23, 2015 to February 20, 2015May 29, 2015 to June 26, 2015September 25, 2015 to October 23, 2015January 22, 2016 to February 19, 2016May 27, 2016 to June 24, 2016September 23, 2016 to October 21, 2016January 20, 2017 to February 17, 2017May 26, 2017 to June 23, 2017September 29, 2017 to October 27, 2017January 19, 2018 to February 16, 2018May 25, 2018 to June 22, 2018September 28, 2018 to October 26, 2018
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  • Predictive Analytics 2 - Neural Nets and Regression This course covers the two core paradigms that account for most business applications of predictive modeling: classification and prediction. The course includes hands-on work with XLMiner, a data-mining add-in for Excel. Tuition: $469 (5.0 CEUs) New available dates:
    August 22, 2014 to September 19, 2014November 28, 2014 to December 26, 2014February 27, 2015 to March 27, 2015July 03, 2015 to July 31, 2015October 30, 2015 to November 27, 2015February 26, 2016 to March 25, 2016July 01, 2016 to July 29, 2016October 28, 2016 to November 25, 2016February 24, 2017 to March 24, 2017June 30, 2017 to July 28, 2017October 27, 2017 to November 24, 2017February 23, 2018 to March 23, 2018June 29, 2018 to July 27, 2018October 26, 2018 to November 23, 2018
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  • Predictive Analytics 3: Dimension Reduction, Clustering and Association Rules 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: $499 (5.0 CEUs) New available dates:
    October 17, 2014 to November 14, 2014January 02, 2015 to January 30, 2015April 17, 2015 to May 15, 2015August 07, 2015 to September 04, 2015January 01, 2016 to January 29, 2016April 15, 2016 to May 13, 2016August 05, 2016 to September 02, 2016January 06, 2017 to February 03, 2017April 14, 2017 to May 12, 2017August 04, 2017 to September 01, 2017January 05, 2018 to February 02, 2018April 13, 2018 to May 11, 2018August 03, 2018 to August 31, 2018
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  • Risk Simulation and Queuing This course covers modeling technique making decisions in the presence of risk or uncertainty.  Specific topics include risk analysis using Monte Carlo simulation for risk simulation, queuing theory for problems involving waiting lines, and decision trees for analyzing problems with multiple discrete decision alternatives.
     
    Tuition: $549 (5.0 CEUs) New available dates:
    November 21, 2014 to December 19, 2014May 01, 2015 to May 29, 2015November 20, 2015 to December 18, 2015May 06, 2016 to June 03, 2016November 18, 2016 to December 16, 2016May 05, 2017 to June 02, 2017November 17, 2017 to December 15, 2017May 04, 2018 to June 01, 2018November 16, 2018 to December 14, 2018
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Elective Courses (3 required)

  • Advanced Optimization This course covers a number of advanced topics in optimization.  You will learn: 1) how to formulate and solve network flow problems, 2) how to model and solve optimization problems where some or all of the decision variables must be integers, 3) how to deal with multiple objectives in optimization problems, and 4) techniques for handling optimization problems where the objective function or constraints are not linear functions of the decision variables. Tuition: $549 (5.0 CEUs) New available dates:
    September 26, 2014 to October 24, 2014September 25, 2015 to October 23, 2015September 23, 2016 to October 21, 2016September 22, 2017 to October 20, 2017September 21, 2018 to October 19, 2018
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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: $549 (5.0 CEUs) New available dates:
    October 31, 2014 to November 28, 2014June 05, 2015 to July 03, 2015June 03, 2016 to July 01, 2016June 02, 2017 to June 30, 2017June 01, 2018 to June 29, 2018
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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: $549 (5.0 CEUs) New available dates:
    January 16, 2015 to February 13, 2015January 15, 2016 to February 12, 2016January 13, 2017 to February 10, 2017January 12, 2018 to February 09, 2018
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  • Financial Risk Modeling This course teaches participants how to model financial events that have uncertainties associated with them. Tuition: $549 (5.0 CEUs) New available dates:
    May 15, 2015 to June 12, 2015May 13, 2016 to June 10, 2016
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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: $549 (5.0 CEUs) New available dates:
    September 05, 2014 to October 03, 2014March 13, 2015 to April 10, 2015September 04, 2015 to October 02, 2015March 11, 2016 to April 08, 2016September 02, 2016 to September 30, 2016
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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: $469 (5.0 CEUs) New available dates:
    March 06, 2015 to April 03, 2015July 17, 2015 to August 14, 2015March 04, 2016 to April 01, 2016July 15, 2016 to August 12, 2016March 03, 2017 to March 31, 2017July 14, 2017 to August 11, 2017March 02, 2018 to March 30, 2018July 13, 2018 to August 10, 2018
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  • Political Analytics This course will teach you how to apply predictive modeling methods to target voters in political campaigns. Tuition: $549 (5.0 CEUs) New available dates:
    August 29, 2014 to September 26, 2014March 06, 2015 to April 03, 2015August 28, 2015 to September 25, 2015March 04, 2016 to April 01, 2016August 26, 2016 to September 23, 2016March 03, 2017 to March 31, 2017August 25, 2017 to September 22, 2017March 02, 2018 to March 30, 2018August 24, 2018 to September 21, 2018
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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: $549 (5.0 CEUs) New available dates:
    October 31, 2014 to November 28, 2014May 08, 2015 to June 05, 2015October 30, 2015 to November 27, 2015April 08, 2016 to May 06, 2016October 28, 2016 to November 25, 2016April 07, 2017 to May 05, 2017October 27, 2017 to November 24, 2017April 06, 2018 to May 04, 2018November 02, 2018 to November 30, 2018
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  • Survival Analysis The course describes the various methods used for modeling and evaluating survival data, or time-to event data. Tuition: $549 (5.0 CEUs) New available dates:
    September 19, 2014 to October 17, 2014March 13, 2015 to April 10, 2015September 18, 2015 to October 16, 2015March 11, 2016 to April 08, 2016September 16, 2016 to October 14, 2016March 10, 2017 to April 07, 2017September 15, 2017 to October 13, 2017March 09, 2018 to April 06, 2018September 14, 2018 to October 12, 2018
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Earn a Certificate

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 and Prerequisites

  1. A Bachelor's degree from an accredited college or university.
  2. The successful recent completion of an introductory statistics course equivalent to Statistics.com's Statistics 1 and Statistics 2,* (please provide proof in your PASS application).

*If you do not meet this requirement, you may still enroll in PASS. Upon review of your application, we will determine whether you need to take Statistics.com's Statistics 1 and 2. If you do require these foundational courses, we will register you for them and waive the entire tuition fee for these two courses.


Procedure for Enrollment and Matriculation in PASS

  1. Complete and submit the application, your photograph, and the payment of the application fee. Notification of approval is sent usually within one week.
  2. After your application is approved, enroll in the PASS of your choice here and pay the enrollment fee.
  3. If you have NOT already met the introductory statistics requirement, you will be registered for the Institute's Statistics 1 and 2 courses. Full tuition is waived for matriculated PASS candidates.
  4. After you submit your application and receive approval, pay the enrollment fee, and meet the introductory statistics requirement, you will be matriculated into the program and are considered a PASS candidate. You may now register for classes as a PASS candidate and receive our academic tuition deduction - specify PASS as your academic affiliation during the online registration process.

Rules and Policies

  • Once you are matriculated in PASS, you are considered a student at the Institute for Statistics Education at Statistics.com.
  • You must be a fully-matriculated PASS candidate to be eligible to receive the academic tuition deduction provided during online registration, and to receive PASS credit for courses.
  • The Program enrollment fee is a required one-time charge in addition to tuition for individual courses.
  • You are expected to complete all the courses in your Program within 5 years of your matriculation into the program. Any exceptions must be approved in writing by the Institute prior to that 5-year deadline.
  • Upon completion of your PASS, you will receive a Certificate and your official transcript.
  • Up to three Institute courses may be taken prior to enrolling in PASS; credit for these courses may be applied to your PASS transcript once you are a matriculated PASS candidate, provided that adequate marks are earned.

Description

Since its founding in 2002, the Institute has been the global pioneer and leader in online statistics and analytics education.  The Institute now offers 100+ online courses in statistics and analytics, plus four certificate programs.

The Analytics for Data Science certificate program focuses on those courses relevant for the study of topics in data analytics (data mining, predictive modeling, forecasting and more).  Most courses are 4 weeks long, do not require you to be online at specific times during the week, and offer continuing education credits.  The workload for the entire program is the equivalent of 16 credits in the U.S. academic system.

The courses are taught by recognized authorities with whom you share a private discussion forum for the entire course period.

Most certificate program candidates choose to take one course at a time.  With courses starting every week of the year, there is considerable scheduling flexibility.  Admission applications are accepted on a rolling basis throughout the year.

Program Objectives

The program consists of eleven 4-week courses.  You will learn how to:

  • Choose and fit time-series forecasting models
  • Construct predictive models using a variety of statistical and machine learning algorithms, and assess their performance
  • Identify customer segments and generate purchase recommendations
  • Use interactive graphical techniques to visualize and analyze data
  • Solve constrained optimization problems using linear programming and other techniques 
  • Describe, visualize and analyze social network data
  • Conduct Monte Carlo simulation to account for risk
  • Specify and solve queuing problems
  • Analyze location and other spatial data (elective)
  • Apply the key concepts in natural language processing (elective)
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From a Student Profile:

I realized one of my work projects would benefit from deeper statistical analysis, including functions I had a good background in and knew at one time, but I needed to dust the cobwebs off and catch up to changes in the field.

Douglas D. Reimel, Jr.

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