Programming for Data Science Certificate – R for Experienced Programmers

This certificate program will advance your R programming skills and help you master its use to build predictive models, machine learning algorithms, and unearth customer and predictive analytics, using R.

Home Certificates Programming for Data Science Certificate – R for Experienced Programmers

Overview

Our Programming for Data Science Certificate for experienced programmers will help you take your R skills to the next level. This ten course program – including eight required courses and two electives – will enable you to become an expert in creating predictive models, understanding machine learning algorithms, and unearthing customer and predictive analytics, using R.

The core curriculum, taught by leading experts in this industry, covers R Programming, SQL, Forecasting and Customer Analytics using R. You’ll also get a deep dive in predictive analytics so you’ll be able to apply your skills immediately at your current job or leverage them as you seek more advanced career opportunities.

This certificate is considered the equivalent of a Master’s degree program and earns 28 course credits in the U.S. academic system which are transferable as college credit – via the American Council on Education – to other institutions in the U.S. See course offerings below.

Please note: The Programming for Data Science Certificate Program is available in four levels. Be sure to choose the one that is right for you:

Novice Python Programmers | Python Experienced Programmers | Novice R Programmers | Experienced R Programmers

Who This Certificate Serves

If you are you an experienced R programmer working – or seeking a job – in data science, you'll be pleased to know that according to online job sites R is the programming language most widely used among statisticians and data miners for developing statistical software and data analysis. Related job titles include:

Data Scientist
Technical Analyst
Statistician
Risk Manager/Director

Systems Engineer
IT Programmers/Developers
Statistician
Researcher

Learning Outcomes

At the completion of the program, you will know how to build data products and unearth customer and predictive analytics, using R. More specifically, you will be able to:

Use and be an expert in R for data analytics and data mining
Read, understand, modify, and create complex functions to perform a variety of tasks.
Implement best programming practices and the development of clear, concise code
Manipulate data programmatically using R functions of your own design
Extract data from a relational database using SQL, and merge it into a single file in R, so that you can perform statistical operations

Understand and deploy predictive models: classification and prediction
Extract, clean, prepare, and mine real data for a predictive model
Understand how to unearth and analyze data in the customer lifecycle
Integrate supervised and unsupervised learning techniques
Choose an appropriate time series model, fit the model, to conduct diagnostics, and use the model for forecasting

Prerequisites

You should be familiar with introductory statistics; if needed we can enroll you in Statistics 1 and Statistics 2 at no charge. We also assume you are an experienced R programmer.

If you are still somewhat new to R, you may want to enroll in our Certificate for Programming for Data Science for Novice Programmers.

Statistics 1 – Probability and Study Design

This course, the first of a three-course sequence, provides an introduction to statistics for those with little or no prior exposure to basic probability and statistics.

Topic: Statistics, Introductory Statistics | Skill: Introductory | Credit Options: ACE, CAP, CEU
Class Start Dates: Dec 3, 2021, Jan 7, 2022, Feb 4, 2022

Statistics 2 – Inference and Association

This course, the second of a three-course sequence, will teach you the use of inference and association through a series of practical applications, based on the resampling/simulation approach, and how to test hypotheses, compute confidence intervals regarding proportions or means, computer correlations, and use of simple linear regressions.

Topic: Statistics, Introductory Statistics | Skill: Introductory | Credit Options: ACE, CEU
Class Start Dates: Dec 10, 2021, Jan 7, 2022, Feb 11, 2022

Required Courses

The Programming for Data Science Certificate Program consists of ten 4-week courses offered completely online at Statistics.com. Below find the eight required courses you will need to take:

Customer Analytics in R

In this course you will work through a customer analytics project from beginning to end, using R.

Topic: Analytics, Marketing Analytics, Using R | Skill: Introductory | Credit Options: ACE, CAP, CEU
Class Start Dates: May 13, 2022, Nov 11, 2022, May 12, 2023

Forecasting Analytics

This course will teach you how to choose an appropriate time series model: fit the model, conduct diagnostics, and use the model for forecasting.

Topic: Analytics, Prediction/Forecasting | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Mar 11, 2022, Jul 8, 2022, Nov 11, 2022, Mar 10, 2023, Jul 7, 2023, Nov 10, 2023, Mar 8, 2024

Predictive Analytics 1 – Machine Learning Tools with R

This course introduces to the basic predictive modeling paradigm: classification and prediction.

Topic: Data Science, Analytics, Machine Learning, Prediction/Forecasting, Using R | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Jan 14, 2022, May 13, 2022

Predictive Analytics 2 – Neural Nets and Regression with R

As a continuation of Predictive Analytics 1, this course introduces to the basic concepts in predictive analytics, with a focus on R, to visualize and explore predictive modeling.

Topic: Data Science, Analytics, Machine Learning, Prediction/Forecasting, Using R | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Mar 11, 2022, Jul 8, 2022

Predictive Analytics 3 – Dimension Reduction, Clustering, and Association Rules with R

This course, with a focus on R, will teach you key unsupervised learning techniques of association rules – principal components analysis, and clustering – and will include an integration of supervised and unsupervised learning techniques.

Topic: Data Science, Analytics, Machine Learning, Prediction/Forecasting, Using R | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Jan 14, 2022, May 13, 2022

Predictive Analytics – Project Capstone

A predictive modeling practicum for the predictive analytices course program.

Topic: Analytics, Machine Learning | Skill: Introductory, Intermediate | Credit Options: CEU
Class Start Dates: Mar 11, 2022

R Programming – Intermediate

This course will teach experienced data analysts 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.

Topic: Data Science, Using R | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Mar 11, 2022, Sep 9, 2022, Mar 10, 2023

SQL – Introduction to Database Queries

This course will teach you how to extract data from a relational database using SQL and merge data into a single file in R so that you can perform statistical operations.

Topic: Data Science, SQL | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Mar 11, 2022

Elective Courses

In addition to the required courses for the Programming for Data Science Certificate Program, you must choose two electives from the list below to complete your program:

Regression Analysis

This course will teach you how multiple linear regression models are derived, assumptions in the models, how to test whether data meets assumptions, and develop strategies for building and understanding useful models.

Topic: Statistics, Statistical Modeling | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Jan 14, 2022, May 6, 2022, Oct 7, 2022

Spatial Statistics for GIS Using R

This course will teach you spatial statistical analysis methods to address problems in which spatial location. This course will explain and give examples of the analysis that can be conducted in a geographic information system such as ArcGIS or Mapinfo.

Topic: Statistics, Analytics, Data Exploration, Statistical Modeling, Using R | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Jan 7, 2022, Jul 8, 2022

Visualization in R with ggplot2

This course will teach you ggplot as an implementation of the grammar of graphics in R. ggplot combines the advantages of base and lattice graphics while maintaining the ability to build up a plot step by step from multiple data sources.

Topic: Data Science, Using R | Skill: Intermediate | Credit Options: CAP, CEU

Matrix Algebra

This course will teach you 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.

Topic: Statistics, Statistical Modeling | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Mar 25, 2022

Multivariate Statistics

This course will teach you key multivariate procedures such as multivariate analysis of variance (MANOVA), principal components, factor analysis, and classification.

Topic: Statistics, Statistical Modeling | Skill: Intermediate, Advanced | Credit Options: CEU
Class Start Dates: Jan 28, 2022, Jul 22, 2022, Jan 27, 2023

Course Calendar

You can get started with any of these courses:

R Programming – Intermediate
SQL – Introduction to Database Queries
Predictive Analytics 1
Forecasting Analytics
Customer Analytics in R

Try it out: take one of the courses, then apply it retroactively to your certificate program after you enroll.

Predictive Analytics 1 - Machine Learning Tools with R	(4-week class)	Jan 14, 2022
Predictive Analytics 3 - Dimension Reduction, Clustering, and Association Rules with R	(4-week class)	Jan 14, 2022
Forecasting Analytics	(4-week class)	Mar 11, 2022
Predictive Analytics - Project Capstone	(4-week class)	Mar 11, 2022
Predictive Analytics 2 - Neural Nets and Regression with R	(4-week class)	Mar 11, 2022
R Programming - Intermediate	(4-week class)	Mar 11, 2022
SQL - Introduction to Database Queries	(4-week class)	Mar 11, 2022
Customer Analytics in R	(4-week class)	May 13, 2022
Predictive Analytics 1 - Machine Learning Tools with R	(4-week class)	May 13, 2022
Predictive Analytics 3 - Dimension Reduction, Clustering, and Association Rules with R	(4-week class)	May 13, 2022

What Our Students Say

This was a great introduction to Programming in R. I feel like I have some basic concepts down and I am looking forward to taking more courses to keep developing my skills in this programming language. I can definitely see the potential for data analysis in my work!

Peter Weddel

Stratus Ag Research

The course, Introduction to R Programming Part Two, taught by Joris Meys was EXCELLENT! All of the course materials were extremely helpful in allowing me not only to understand the details of R programming but also to gain a solid perspective on the fundamentals of R coding. The feedback on the assignments was very detailed and the explanations included why certain approaches of coding were preferable to others. I really enjoyed this course and I learned a great deal.

Margaret Palmisano

Tuition and Fees

Our Programming for Data Science Certificate Program – the equivalent of a Master’s Degree in content and topical coverage – is a fraction of the cost of what you would pay at a University. The workload is equal to 28 credits in the U. S. academic system which are transferable via the American Council on Education. Choose to pay as you go, or get a discount for paying in full today.

Pay As You Go

$5,677

Pay In Advance

$5,000

Payment options

$5000 one-time fee [best value]

$290/month for 18 months [$5220]

$495 enrollment + course fees [$5750]

Frequently Asked Questions

Are there admission requirements?

You should have recently had introductory statistics, equivalent to our Statistics 1 and Statistics 2 courses. If you haven’t, or if you’d like to go over that basic material again as a refresher course, we’ll put enroll in Statistics 1 and Statistics 2 at no charge once we accept your application.

Please see our knowledge center for more information.

Is there an application deadline for the certificate program?

Applications are accepted year-round on a rolling basis and courses begin every month.

What if courses in the series don’t match what I need?

If courses in our program don’t match what you need, we can create a custom program for you. Tell us what you have in mind, and we can work together to create a program that makes sense.

Are the certificate programs accredited?

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

In addition, many of the courses at The Institute for Statistics Education have been recommended for credit by The American Council on Education (ACE), INFORMS, and can be used as CEUs in many programs.

The American Council on Education (ACE) approved credit for many of the required courses for our certificate programs and can be transferred to another educational institution that accepts ACE credit.

How long do I have to complete the 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 three (3) years to complete the certificate.

Please see our knowledge center for more information.

Visit our knowledge base and learn more.

Related Blogs

“Defiant” Supervision

How did the phrase "defiantly recommend", as in "I defiantly recommend this product," come into common usage on the internet? The answer is a good look inside the workings of supervised learning. Supervision, generally from humans, is instrumental in much of statistical and machine learning. Google's precise search algorithms...

Need More Information?

Additional Series Information

Organization of Program

The certificate program includes are all standard Statistics.com courses – small classes, regular interaction with your instructor throughout the course, rapid expert feedback on your homework and projects. You can register for the courses individually, and even incorporate courses that you have recently successfully completed.

Time Requirements

There are 10 courses, each are 4 weeks long. You may build your own course calendar to meet your individual requirements. The certificate program can be completed in a year or two, depending on your personal schedule and course availability.

Course Fee & Information

The fee for the Programming for Data Science Certificate Program if you pay in full is only $5,000. This includes the program registration fee, and individual course fees. It reflects considerable savings that are available if you pay the program cost upon enrollment. Note: all tuition held on account must be used within two (2) years from date of purchase.

You also have the option to pay on a course-by-course basis with our pay as you go model estimated fee of $5,632. You will need to pay the registration fee to enroll which is $495. The “pay-as-you-go” estimate includes the registration fee, individual course fees (required: $3,832 and estimated electives:$975) that you pay as you progress through the program, as well as various tuition savings available to you once you are a matriculated certificate candidate at the Institute. The actual total cost of the program may vary slightly depending on several factors and may differ slightly from the estimate above; fees are subject to change without prior notice.

Options for Credit and Recognition

Our Programming for Data Science Certificate Program – the equivalent of a Mastery Degree – is the equal to 28 credits in the U. S. academic system which are transferable via the American Council on Education. More details on ACE and accreditation can be found here.

Miscellaneous

Visit our knowledge base to learn more about our certificate programs.