Programming for Data Science

Online Certificate Program

Programming for Data Science Certificate Program

This program is for you if:

  • You are a programmer and want to learn how to harness predictive models, machine learning algorithms, and statistical methods in your work
  • You are an IT or database professional and looking to learn the programming tools for analytics
  • You are a statistician and need to expand your skill set in to the Big Data programming realm.

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 Programming in 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 16.5 credits in the U.S. academic system.  At the completion of the program you will have learned how to:

  • Program in R (4 course sequence, with exam)
  • Use Python for data analytics
  • Do text mining with Python and nltk
  • Query databases with SQL
  • Write and deploy MapReduce jobs for Hadoop
  • Use R for data mining
  • Extract, clean, prepare, and mine real data in a practicum, culminating the prototyping of a predictive model

 

Planning my Program

Course ListExplore elective options, including suggested concentration strands

Thanks

TimelineView a typical sequence of courses


FULL PROGRAM LIST

Required Courses (8)

  • Applied Predictive Analytics
    A predictive modeling practicum Tuition: $549 (5.0 CEUs) Next three dates:
    January 01, 2016 to January 29, 2016July 01, 2016 to July 29, 2016January 06, 2017 to February 03, 2017June 30, 2017 to July 28, 2017January 05, 2018 to February 02, 2018June 29, 2018 to July 27, 2018
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  • Big Data Computing with Hadoop
    This online class, "Introduction to Analytics using Hadoop" will introduce analytics professionals to Hadoop, Spark, MapReduce, and provide an exemplar workflow for using Hadoop, and finally leveraging Hadoop Streaming to conclude work in an analytics programming language such as Python. Tuition: $469 (5.0 CEUs) Next three dates:
    October 30, 2015 to November 27, 2015March 25, 2016 to April 22, 2016October 28, 2016 to November 25, 2016March 24, 2017 to April 21, 2017October 27, 2017 to November 24, 2017March 23, 2018 to April 20, 2018October 26, 2018 to November 23, 2018
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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: $469 (5.0 CEUs) Next three dates:
    October 09, 2015 to November 06, 2015February 05, 2016 to March 04, 2016June 24, 2016 to July 22, 2016October 14, 2016 to November 11, 2016February 03, 2017 to March 03, 2017June 23, 2017 to July 21, 2017October 13, 2017 to November 10, 2017February 02, 2018 to March 02, 2018June 22, 2018 to July 20, 2018October 12, 2018 to November 09, 2018
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  • Introduction to Python for Analytics
    In this course you'll learn basic Python skills and data structures, move on to how to load data from different sources, rearrange and aggregate it, and finally how to analyze and visualize it to create high-quality products. Tuition: $469 (5.0 CEUs) Next three dates:
    September 11, 2015 to October 09, 2015January 08, 2016 to February 05, 2016May 13, 2016 to June 10, 2016September 09, 2016 to October 07, 2016January 13, 2017 to February 10, 2017May 12, 2017 to June 09, 2017September 08, 2017 to October 06, 2017January 12, 2018 to February 09, 2018May 11, 2018 to June 08, 2018September 07, 2018 to October 05, 2018
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  • Introduction to SAS Programming for Analytics
    This course covers the basic programming and data handling capabilities of SAS. Tuition: $469 (5.0 CEUs) Next three dates:
    October 09, 2015 to November 06, 2015January 15, 2016 to February 12, 2016April 15, 2016 to May 13, 2016October 07, 2016 to November 04, 2016January 13, 2017 to February 10, 2017April 14, 2017 to May 12, 2017October 06, 2017 to November 03, 2017
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  • R Programming - Intermediate

    This course is intended for experienced data analysts looking to unlock the power of R.  It provides a systematic overview of R as a programming language, emphasizing good programming practices and the development of clear, concise code.  After completing the course, students should be able to manipulate data programmatically using R functions of their own design.

    Tuition: $489 (5.0 CEUs) Next three dates:
    September 25, 2015 to October 23, 2015April 01, 2016 to April 29, 2016September 23, 2016 to October 21, 2016March 31, 2017 to April 28, 2017September 22, 2017 to October 20, 2017March 30, 2018 to April 27, 2018September 21, 2018 to October 19, 2018
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  • SQL and R - Introduction to Database Queries
    The purpose of this course is to teach you how to extract data from a relational database using SQL, and merge it into a single file in R, so that you can perform statistical operations. Tuition: $469 (5.0 CEUs) Next three dates:
    November 13, 2015 to December 11, 2015March 18, 2016 to April 15, 2016August 05, 2016 to September 02, 2016November 11, 2016 to December 09, 2016March 17, 2017 to April 14, 2017August 04, 2017 to September 01, 2017November 10, 2017 to December 08, 2017March 16, 2018 to April 13, 2018August 03, 2018 to August 31, 2018November 09, 2018 to December 07, 2018
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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: $469 (5.0 CEUs) Next three dates:
    February 05, 2016 to March 04, 2016June 10, 2016 to July 08, 2016February 03, 2017 to March 03, 2017June 09, 2017 to July 07, 2017February 02, 2018 to March 02, 2018June 08, 2018 to July 06, 2018
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Elective Courses (3 required)

  • Graphics in R
    The aim of this course is to teach you how to produce statistical plots of data using the R language and environment for statistical computing and graphics. The creation of standard plots such as scatterplots, bar charts, histograms, and boxplots will be covered and time will be spent on the underlying model used to produce plots in R so that you can extensively customize these plots. Tuition: $469 (5.0 CEUs) Next three dates:
    October 09, 2015 to November 06, 2015April 29, 2016 to May 27, 2016October 07, 2016 to November 04, 2016May 05, 2017 to June 02, 2017October 06, 2017 to November 03, 2017May 04, 2018 to June 01, 2018October 05, 2018 to November 02, 2018
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  • Hadoop: Hive, Sqoop and Spark
    This course will introduce statisticians and data analysts to Spark, MapReduce, and higher-order tools in the Hadoop Ecosystem. Tuition: $469 (5.0 CEUs) Next three dates:
    January 22, 2016 to February 19, 2016May 27, 2016 to June 24, 2016January 20, 2017 to February 17, 2017May 26, 2017 to June 23, 2017December 01, 2017 to December 29, 2017June 01, 2018 to June 29, 2018November 30, 2018 to December 28, 2018
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  • Mapping in R

    R provides a very flexible environment for statistical analysis, including a number of facilities to manipulate, visualise and analyse spatial information. Here, the emphasis is on visualising spatial data. A key advantage of mapping in R is that it is very easy to integrate the results of data analysis with the map creation process. In this course, you will discover how to use R as a tool for creating maps, identifying its strengths and weaknesses. the course will explain how spatial data may be written/read and visualized in R, and show how publication quality maps may be produced in R, based on the GISTools package, as well as providing a review of a number of other diverse methods for visually representing geographical information in R.

    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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  • 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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  • Natural Language Processing Using NLTK
    After taking this course you will be equipped to introduce natural language processing (NLP) processes into your projects and software applications. Tuition: $469 (5.0 CEUs) Next three dates:
    April 08, 2016 to May 06, 2016September 16, 2016 to October 14, 2016April 07, 2017 to May 05, 2017September 15, 2017 to October 13, 2017April 06, 2018 to May 04, 2018September 14, 2018 to October 12, 2018
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  • R Programming - Advanced

    This course covers key concepts for writing advanced R code, emphasizing the design of functional and efficient code.  It will set students down the road to mastering the intricacies of R.  After completing the course, students should be able to read, understand, modify, and create complex functions to perform a variety of tasks.

    Tuition: $489 (5.0 CEUs) Next three dates:
    January 08, 2016 to February 05, 2016May 20, 2016 to June 17, 2016January 06, 2017 to February 03, 2017May 19, 2017 to June 16, 2017January 05, 2018 to February 02, 2018May 18, 2018 to June 15, 2018
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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: $389 (3.75 CEUs) Next three dates:
    August 19, 2016 to September 09, 2016August 18, 2017 to September 08, 2017August 17, 2018 to September 07, 2018
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  • Social Data Mining With Python

    Tuition: $469 (5.0 CEUs) Next three dates:
    September 18, 2015 to October 16, 2015March 18, 2016 to April 15, 2016September 23, 2016 to October 21, 2016March 17, 2017 to April 14, 2017September 22, 2017 to October 20, 2017March 16, 2018 to April 13, 2018September 21, 2018 to October 19, 2018
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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: $549 (5.0 CEUs) Next three dates:
    January 29, 2016 to February 26, 2016January 27, 2017 to February 24, 2017January 26, 2018 to February 23, 2018January 25, 2019 to February 22, 2019
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  • Visualization in R with ggplot2

    ggplot, created by Hadley Wickham, is an implementation of the grammar of graphics in R.  It combines the advantages of both base and lattice graphics: conditioning and shared axes are handled automatically, while maintaining the ability to build up a plot step by step from multiple data sources. It also implements a more sophisticated multidimensional conditioning system and a consistent interface to map data to aesthetic attributes.

    ggplot won the 2006 John Chambers Award for Statistical Computing.

    Tuition: $469 (5.0 CEUs) Next three dates:
    January 15, 2016 to February 12, 2016July 22, 2016 to August 19, 2016January 13, 2017 to February 10, 2017July 21, 2017 to August 18, 2017January 12, 2018 to February 09, 2018July 20, 2018 to August 17, 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: $3852
Estimated Electives Course Tuition: $1437
Estimated Material Cost: $770
Estimated Total Cost: $6729

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, and some familiarity with programming*.

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.

*If you have no programming background, we can still help you.  Mention on your application that you need to speak to a counselor about this. 

 

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 am working for Scotiabank/International Banking-Marketing (Toronto-Canada). Since we are manipulating tons of data at the customer level for more than 27 countries, R would be the perfect complement tool (we have been using SAS) for customer analytics. I am new on this R world but I would like to apply it on a daily basis soon."

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