Programming for Data Science: R (for novice programmers)

Online Certificate Program

10 courses, 4 weeks each
$5,000

Programming for Data Science Certificate Program: R

(for novice programmers)

This program is for you if:

  • You are new to programming and want to learn how to harness R to build predictive models, machine learning algorithms, and statistical methods in your work

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 roughly 30 credits in the U.S. academic system.  At the completion of the program you will have learned how to:

  • Program in R 
  • Use R for data analytics and data mining
  • Query databases with SQL
  • Extract, clean, prepare, and mine data in a practicum, culminating the prototyping of a predictive model

Compare Statistics.com certificates to other graduate programs in analytics and data science

 

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

 
 

FULL PROGRAM LIST

Required Courses (8)

  • Customer Analytics in R
    Tuition: $469.00 (5.0 CEUs) Next three dates:
    May 24, 2019 to June 21, 2019November 22, 2019 to December 20, 2019May 22, 2020 to June 19, 2020November 20, 2020 to December 18, 2020May 21, 2021 to June 18, 2021
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  • 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:
    January 18, 2019 to February 15, 2019May 10, 2019 to June 07, 2019September 27, 2019 to October 25, 2019January 17, 2020 to February 14, 2020May 22, 2020 to June 19, 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:
    February 22, 2019 to March 22, 2019July 12, 2019 to August 09, 2019November 15, 2019 to December 13, 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 3: Dimension Reduction, Clustering and Association Rules - with R
    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: $469.00 (5.0 CEUs) Next three dates:
    January 04, 2019 to February 01, 2019April 12, 2019 to May 10, 2019September 06, 2019 to October 04, 2019January 03, 2020 to January 31, 2020April 10, 2020 to May 08, 2020July 31, 2020 to August 28, 2020
    show more dates >> Learn more and register >>
  • Predictive Analytics Project Capstone
    A predictive modeling practicum Tuition: $499 (5.0 CEUs) Next three dates:
    March 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 >>
  • R Programming - Introduction 1
    This course will provide an easy introduction to programming in R. Tuition: $469 (5.0 CEUs) Next three dates:
    December 14, 2018 to January 11, 2019January 11, 2019 to February 08, 2019May 10, 2019 to June 07, 2019September 06, 2019 to October 04, 2019January 17, 2020 to February 14, 2020May 29, 2020 to June 26, 2020September 25, 2020 to October 23, 2020
    show more dates >> Learn more and register >>
  • R Programming - Introduction 2
    This course continues the introduction to R programming. Tuition: $469 (5.0 CEUs) Next three dates:
    March 15, 2019 to April 12, 2019July 12, 2019 to August 09, 2019November 15, 2019 to December 13, 2019March 13, 2020 to April 10, 2020July 17, 2020 to August 14, 2020November 13, 2020 to December 11, 2020March 12, 2021 to April 09, 2021
    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:
    March 15, 2019 to April 12, 2019July 12, 2019 to August 09, 2019November 15, 2019 to December 13, 2019March 13, 2020 to April 10, 2020July 31, 2020 to August 28, 2020March 12, 2021 to April 09, 2021July 30, 2021 to August 27, 2021
    show more dates >> Learn more and register >>

Elective Courses (2 required)

  • 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:
    March 22, 2019 to April 19, 2019July 26, 2019 to August 23, 2019November 22, 2019 to December 20, 2019March 20, 2020 to April 17, 2020July 24, 2020 to August 21, 2020November 20, 2020 to December 18, 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:
    May 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 >>
  • 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: $499 (5.0 CEUs) Next three dates:
    January 18, 2019 to February 15, 2019May 10, 2019 to June 07, 2019October 04, 2019 to November 01, 2019January 17, 2020 to February 14, 2020May 08, 2020 to June 05, 2020October 02, 2020 to October 30, 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:
    January 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 to pay on a course-by-course basis:

  • Pay for your program upon enrollment:  $5000
  • Pay as you go: $5,597

 

Detailed Fees Description

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Student Profile

The Statistics.com courses have helped me a lot, pushing me to the limit and making me learn much more than I expected I could. The knowledge I gained I could immediately leverage in my job ... then eventually led to landing a job in my dream company - Amazon.

 

Karolis Urbonas
Senior Data Scientist, Amazon Europe

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