Programming for Data Science Certificate – R for Novice Programmers

Programming for Data Science Certificate – R for Novice Programmers

This Certificate Program will empower you to use R to build predictive models, develop visualizations, design machine learning algorithms, and integrate statistical methods in your work or learning practicum.
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Overview

Our Programming for Data Science Certificate for novice programmers will help you harness R to build predictive models, develop visualizations, design machine learning algorithms, and integrate statistical methods in your work or learning practicum.

The core curriculum, taught by leading experts in this industry, covers everything from R programming fundamentals to database queries, as well as a deep dive into predictive and customer analytics so you can apply your skills immediately at your current job or leverage them as your career dictates.

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

10-Course Certificate Program
ACE + CAP Credit Eligible
Online Course
Flexible Schedule
Teacher Assistant Support
Expert Instructors

Who This Certificate Serves

If you are new to programming and want to learn how to use R for data science, you're on the right track. Jobs in data science are largely seen among the best career paths out there with programmers always needed to build data products and software platforms in nearly every industry. Related job titles include:
  • Data Scientist
  • Technical Analyst
  • Statistician
  • Risk Manager/Director
  • Systems Engineer
  • IT Programmers/Developers
  • Statistician
  • Researcher

Learning Outcomes

In this data-driven world, programmers are a hot commodity and needed to create predictive models, develop visualizations, design machine learning algorithms, and integrate statistical methods for businesses around the globe. The Programming for Data Science Certificate will deliver that and more. More specifically, you will be able to:
  • Read, understand, modify, and create basic functions using R to perform a variety of tasks.
  • Manipulate data programmatically using R for data analytics and data mining
  • Extract data from a relational database using SQL, and merge it into a single file in R, so that you can perform statistical operations
  • Extract, clean, prepare, and mine data in a practicum, culminating the prototyping of a predictive model
  • Understand and deploy predictive models: classification and prediction
  • Understand how to unearth and analyze data in the customer lifecycle

Prerequisites

You should be familiar with introductory statistics; if needed we can enroll you in “Introductory Stats for Credit” at no charge.

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Introductory Statistics for College Credit

Introductory Statistics for Credit

This course will teach you the equivalent of a semester course in introductory statistics.
Topic: Statistics, Introductory Statistics | Skill: Introductory | Credit Options: ACE, CEU
Class Start Dates: Apr 7, 2023, May 5, 2023, Jun 2, 2023, Jul 7, 2023, Aug 4, 2023, Sep 1, 2023, Oct 6, 2023, Nov 3, 2023, Dec 1, 2023, Jan 5, 2024, Feb 2, 2024, Mar 1, 2024, Apr 5, 2024, May 3, 2024

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:

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Customer Analytics in R

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 12, 2023, Nov 10, 2023, May 10, 2024, Nov 8, 2024
Mapping in R Course

Predictive Analytics 1 with R – Machine Learning Tools

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: May 12, 2023, Sep 8, 2023, Jan 12, 2024
Predictive Analytics 2 – Neural Nets and Regression with R

Predictive Analytics 2 with R – Neural Nets and Regression

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: Jul 7, 2023, Nov 10, 2023, Mar 8, 2024
R Programming - Intermediate

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

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: May 12, 2023, Sep 8, 2023, Jan 12, 2024
Predictive Analytics – Project Capstone

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: Sep 8, 2023, Mar 8, 2024
R Programming - Introduction Part 1

Introduction to R Programming

This course provides an easy introduction to programming in R.
Topic: Data Science, Using R | Skill: Introductory | Credit Options: ACE, CAP, CEU
Class Start Dates: May 12, 2023, Sep 8, 2023, Jan 12, 2024
Mapping in R Course

R Programming – Introduction Part 2

This course is a continuation of the introduction to R programming.
Topic: Data Science, Using R | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Jul 7, 2023, Nov 10, 2023, Mar 8, 2024
Mapping in R Course

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: Jul 7, 2023, Nov 10, 2023, Mar 8, 2024, Jul 5, 2024

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:

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Regression Analysis

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: May 5, 2023, Oct 13, 2023, Jan 12, 2024
Spatial Statistics for GIS Using R

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: Jul 7, 2023, Jan 12, 2024, Jul 12, 2024
Mapping in R Course

Mapping in R

This course will teach you how spatial data may be visualized in R and provides a review of a number of other diverse methods for visually representing geographical information in R.
Topic: Analytics, Data Exploration, Using R | Skill: Intermediate | Credit Options: CAP, CEU
Class Start Dates: Jun 2, 2023, Jun 7, 2024
Forecasting Analytics

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: Jul 7, 2023, Nov 10, 2023, Mar 9, 2024, Jul 5, 2024, Nov 8, 2024

Course Calendar

You can get started with either of these courses:

  • R Programming – Introduction Part 1
  • SQL – Introduction to Database Queries

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

Customer Analytics in R(4-week class)May 12, 2023
Introduction to R Programming(4-week class)May 12, 2023
Predictive Analytics 1 with R - Machine Learning Tools(4-week class)May 12, 2023
Predictive Analytics 3 with R - Dimension Reduction, Clustering, and Association Rules(4-week class)May 12, 2023
Predictive Analytics 2 with R - Neural Nets and Regression(4-week class)Jul 7, 2023
R Programming - Introduction Part 2(4-week class)Jul 7, 2023
SQL - Introduction to Database Queries(4-week class)Jul 7, 2023
Introduction to R Programming(4-week class)Sep 8, 2023
Predictive Analytics - Project Capstone(4-week class)Sep 8, 2023
Predictive Analytics 1 with R - Machine Learning Tools(4-week class)Sep 8, 2023

What Our Students Say​

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Left Square Qoute

This course is an excellent follow up to the R basic course. A lot of new and helpful material was added and contributed to a more advanced understanding of R programming

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David LaBarre
Risk Analyst at USDA-FSIS
Jonathan Jenkins
Left Square Qoute

Great explanations provided by the course instructor in the videos and on the discussion board. The teacher assistant was very diligent and professional in reaching out to me and giving me every opportunity to be successful in this course. Definitely a wonderful experience!

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Jonathan Jenkins
Cobb County Government

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.

Payment options

$6,299 one-time fee [best value]

$369/month for 18 months [$6,642]

$649  enrollment + course fees [$6,948]

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.

FAQs + Knowledge Base

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Additional Series Information

Organization of Program

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

Time Requirements

There are 10 courses, each is 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 $6,299. 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 the 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 $6,890. You will need to pay the registration fee to enroll which is $649. The “pay-as-you-go” estimate includes the registration fee and individual course fees (required: $4,823 and estimated electives:$2,067) 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

Options for Credit and Recognition

Our Programming for Data Science Certificate Program – the equivalent of a Master’s Degree in content and topical coverage – 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.