Analytics for Data Science

Online Certificate Program

Analytics for Data Science Certificate Program

This program is for you if:  

  • You are a business or data analyst needing to add data mining to your skill set to interface with vendors or programmers
  • You are a manager reponsible for analytics teams or vendors
  • You are a data scientist, software engineer, or IT professional seeking a deeper dive into analytics (but see our "Programming for Data Science" certificate if you need to learn the programming tools for this)

Hint:  Check out our job boards page, conduct some job searches, find some jobs you are interested in, and see what skills are needed before you start your program of study.  Statistics.com can help you acquire most of the analytics skills you need.

Program Content

The Analytics for Data Science Certificate Program consists of eleven, 4-week courses offered completely online at Statistics.com. There are required topics and a selection of electives.  The workload for the entire program is the equivalent of 16 credits in the U.S. academic system.  At the completion of the program you will have learned 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)

 

Planning my Program

Course ListExplore elective options, including suggested concentration strands

Thanks

TimelineView a typical sequence of courses


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) Next three dates:
    November 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) Next three dates:
    October 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 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) Next three dates:
    February 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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  • Optimization - Linear Programming
    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) Next three dates:
    January 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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  • 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) Next three dates:
    September 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) Next three dates:
    October 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) Next three dates:
    October 16, 2015 to November 13, 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) Next three dates:
    November 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)

  • Cluster Analysis
    In this online course, “Cluster Analysis,” you will learn 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) Next three dates:
    June 03, 2016 to July 01, 2016June 02, 2017 to June 30, 2017June 01, 2018 to June 29, 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) Next three dates:
    May 13, 2016 to June 10, 2016May 12, 2017 to June 09, 2017May 11, 2018 to June 08, 2018
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  • Integer & Nonlinear Programming and Network Flow
    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) Next three dates:
    September 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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  • 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) Next three dates:
    September 04, 2015 to October 02, 2015November 13, 2015 to December 11, 2015March 11, 2016 to April 08, 2016September 02, 2016 to September 30, 2016March 10, 2017 to April 07, 2017September 01, 2017 to September 29, 2017March 02, 2018 to March 30, 2018August 31, 2018 to September 28, 2018
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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) Next three dates:
    March 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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  • Persuasion Analytics and Targeting
    This course will teach you how to apply predictive modeling methods to identify persuadable individuals, and to target voters in political campaigns. Tuition: $549 (5.0 CEUs) Next three dates:
    August 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) Next three dates:
    October 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) Next three dates:
    September 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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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:$595
Estimated Required Course Tuition: $4002
Estimated Electives Course Tuition: $1623
Estimated Material Cost: $770
Estimated Total Cost: $7065

Is there an application deadline?

No - applications are accepted and students are enrolled year round on a rolling basis. See the timeline tool in the "Program" tab to see the recommended sequence of courses starting in any given month.

 

Are there admission requirements?

We'd like you to have a Bachelor's degree from an accredited college or university.

Also, you should have recently had introductory statistics, equivalent to Statistics.com's Statistics 1 and Statistics 2. If you haven't, or if you'd like to go over that ground again, no worries. We'll put you in Statistics 1 and 2 at no charge once we accept your application! Statistics 1 starts at the beginning of each month.

 

What are the fees?

The application fee is $75, which you can pay here. The enrollment fee is $595, which includes free enrollment in Statistics.com's Statistics 1 and Statistics 2 courses if needed. Once you are enrolled, you pay course tuition fees "as you go," at the discounted academic rate.

 

Is there any particular way I should schedule my courses?

Not really, no.  Scheduling is quite flexible with various courses offered all throughout the year and a class format that does not require you to be online at any specific times.  Most PASS students choose to take one course at a time, but we encourage you to plan your program in a way that fits your schedule and helps you personally learn best.

 

Can I get credit for courses I have already taken at Statistics.com?

Yes. You can apply up to three prior courses to your program, provided you got adequate marks.

 

If I have already mastered a topic from my work or prior academic experience, do I need to repeat it?

No. We do not want to waste your time. Just share with us how you covered the topic and we'll swap out that course for something else.

 

The courses in the PASS programs don't exactly match what I need. Can I craft a custom program?

Maybe. Contact us so we can review what you want to do, and work together to create a program that makes sense!

 

How long do I have to complete the PASS certificate?

Five years.

 

Are the certificate programs accredited?

Most of the individual courses in the Data Science certificate programs have been approved for academic credit recommendation by the American Council on Education (ACE), which makes it relatively easy to transfer academic credit for these courses to another educational institution. Those same courses have also been approved as recognized professional development courses by INFORMS, the Operations Research Society. The Institute for Statistics Education is not itself accredited as an academic institution.

 

Still have questions?

Contact the registrar (ourcourses [at] statistics.com) and we'll try to answer them as well as possible.

 

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Student Profile

I hear IT people commenting that they’re always needing to learn new technology because things in their field evolve and change quickly. The same thing is true in analytics. New techniques are developing rapidly.

Robert Wood
Director, Advanced Analytics Group, Merkle

see the complete student profile

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