Programming for Data Science

Online Certificate Program

10 courses, 4 weeks each
$5,000

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 ten 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
  • Use R for data mining
  • Extract, clean, prepare, and mine real data in a practicum, culminating the prototyping of a predictive model

Compare Statistics.com certificates to university graduate programs, MOOC's, bootcamps...

 

Planning my Program

Course ListView printable list of courses with first available start date.

 
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How to use:
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2. Click "X" on weeks you're unavailable.

In this certificate program, there are '8' required courses + you choose '2' electives

FULL PROGRAM LIST

Required Courses (8)

  • Anomaly Detection
    Tuition: $469 (5.0 CEUs) Next three dates:
    October 19, 2018 to November 16, 2018October 18, 2019 to November 15, 2019October 16, 2020 to November 13, 2020October 15, 2021 to November 12, 2021
    show more dates >> Learn more and register >>
  • Predictive Analytics 1 - Machine Learning Tools - with R
    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 28, 2018 to October 26, 2018January 18, 2019 to February 15, 2019May 24, 2019 to June 21, 2019September 27, 2019 to October 25, 2019January 17, 2020 to February 14, 2020
    show more dates >> Learn more and register >>
  • Predictive Analytics 2 - Neural Nets and Regression - with R
    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:
    June 29, 2018 to July 27, 2018October 26, 2018 to November 23, 2018February 22, 2019 to March 22, 2019June 28, 2019 to July 26, 2019October 25, 2019 to November 22, 2019February 21, 2020 to March 20, 2020June 26, 2020 to July 24, 2020October 23, 2020 to November 20, 2020
    show more dates >> Learn more and register >>
  • Predictive Analytics Project Capstone
    A predictive modeling practicum Tuition: $499 (5.0 CEUs) Next three dates:
    August 24, 2018 to September 21, 2018March 01, 2019 to March 29, 2019August 23, 2019 to September 20, 2019February 28, 2020 to March 27, 2020
    show more dates >> Learn more and register >>
  • 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 07, 2018 to October 05, 2018January 11, 2019 to February 08, 2019May 10, 2019 to June 07, 2019September 06, 2019 to October 04, 2019January 10, 2020 to February 07, 2020May 08, 2020 to June 05, 2020September 04, 2020 to October 02, 2020
    show more dates >> Learn more and register >>
  • 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 21, 2018 to October 19, 2018March 29, 2019 to April 26, 2019September 20, 2019 to October 18, 2019March 27, 2020 to April 24, 2020September 18, 2020 to October 16, 2020
    show more dates >> Learn more and register >>
  • SQL - 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:
    August 03, 2018 to August 31, 2018November 09, 2018 to December 07, 2018March 15, 2019 to April 12, 2019August 02, 2019 to August 30, 2019November 08, 2019 to December 06, 2019March 13, 2020 to April 10, 2020July 31, 2020 to August 28, 2020November 06, 2020 to December 04, 2020
    show more dates >> Learn more and register >>
  • 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 01, 2019 to March 01, 2019June 07, 2019 to July 05, 2019January 31, 2020 to February 28, 2020
    show more dates >> Learn more and register >>

Elective Courses (2 required)

  • Customer Analytics in R
    Tuition: $469.00 (5.0 CEUs) Next three dates:
    November 23, 2018 to December 21, 2018May 24, 2019 to June 21, 2019November 22, 2019 to December 20, 2019May 22, 2020 to June 19, 2020
    show more dates >> Learn more and register >>
  • Deep Learning
    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:
    November 09, 2018 to December 07, 2018November 08, 2019 to December 06, 2019November 06, 2020 to December 04, 2020
    show more dates >> Learn more and register >>
  • 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: $509 (5.0 CEUs) Next three dates:
    November 23, 2018 to December 21, 2018May 03, 2019 to May 31, 2019November 22, 2019 to December 20, 2019May 01, 2020 to May 29, 2020November 20, 2020 to December 18, 2020
    show more dates >> Learn more and register >>
  • 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: $469 (5.0 CEUs) Next three dates:
    August 17, 2018 to September 14, 2018March 29, 2019 to April 26, 2019August 16, 2019 to September 13, 2019March 27, 2020 to April 24, 2020August 14, 2020 to September 11, 2020
    show more dates >> Learn more and register >>
  • 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:
    July 13, 2018 to August 10, 2018March 01, 2019 to March 29, 2019July 12, 2019 to August 09, 2019February 28, 2020 to March 27, 2020
    show more dates >> Learn more and register >>
  • 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:
    September 14, 2018 to October 12, 2018September 13, 2019 to October 11, 2019September 11, 2020 to October 09, 2020
    show more dates >> Learn more and register >>
  • Python for Data Science
    Tuition: $469 (5.0 CEUs) Next three dates:
    October 19, 2018 to November 16, 2018
    show more dates >> Learn more and register >>
  • 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 04, 2019 to February 01, 2019May 17, 2019 to June 14, 2019January 03, 2020 to January 31, 2020May 15, 2020 to June 12, 2020
    show more dates >> Learn more and register >>
  • Spatial Analysis Techniques in R
    This course will teach users how to implement spatial statistical analysis procedures using R software. Tuition: $499 (5.0 CEUs) Next three dates:
    January 25, 2019 to February 22, 2019January 24, 2020 to February 21, 2020
    show more dates >> Learn more and register >>
  • 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:
    July 20, 2018 to August 17, 2018January 11, 2019 to February 08, 2019July 19, 2019 to August 16, 2019January 10, 2020 to February 07, 2020July 17, 2020 to August 14, 2020
    show more dates >> Learn more and register >>

 

Tuition and Fees:  $5000  

The above estimate includes the program registration fee, and individual course fees.  It reflects considerable savings that are available if you pay the program cost upon enrollment.  You also have the option of paying in monthly installments, or on a course-by-course basis:

  • Pay for your program upon enrollment:  $5000
  • Pay as you go: $5,507

 

Detailed Fees Description

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 enrollment fee is $495, 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. A customization fee is charged.

 

How long do I have to complete the PASS certificate?

If you take one course at a time, most programs can be completed in 12-15 months.  We know that sometimes life takes unexpected turns, so you have 3 years to complete the certificate.

 

Are the certificate programs accredited?

  • The American Council on Education (ACE) has recommended academic credit for all the required courses in the Analytics for Data Science Certificate Program, so they can be easily transfered to another educational institution that accepts ACE CREDIT.
  • The Institute for Operations Research and the Management Sciences (INFORMS) chose Statistics.com as a Recognized Analytics Education Provider that supports the Certified Analytics Professional (CAP®) program.
  • Each course has C.E.U.'s granted, based on the length of the course.  (Typically 5.0 CEUs for 4 week courses.)
  • The Institute for Statistics Education itself is not an accredited academic institution, but is

    certified to operate by the State Council of Higher Education for Virginia (SCHEV).


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’ve increased my exposure in my department and profession because I have experience with a number of data analysis approaches. I’ve been asked to give guest lectures in other classes on statistical methods and different strategies, and I was asked to present at a national conference.

Todd Lewis, Ph.D., Associate Professor
Department of Counseling and Educational Development
School of Education
University of North Carolina at Greensboro

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