Programming for Data Science
Online Certificate Program
10 courses, 4 weeks each
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.
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
- 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
Tuition: $469 (5.0 CEUs) Next three dates:October 21, 2016 to November 18, 2016April 21, 2017 to May 19, 2017October 20, 2017 to November 17, 2017April 20, 2018 to May 18, 2018October 19, 2018 to November 16, 2018show more dates >> Learn more and register >>
Applied Predictive Analytics
A predictive modeling practicum Tuition: $499 (5.0 CEUs) Next three dates:August 26, 2016 to September 23, 2016March 03, 2017 to March 31, 2017August 25, 2017 to September 22, 2017March 02, 2018 to March 30, 2018August 24, 2018 to September 21, 2018show more dates >> Learn more and register >>
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 14, 2016 to November 11, 2016March 24, 2017 to April 21, 2017October 27, 2017 to November 24, 2017March 23, 2018 to April 20, 2018October 26, 2018 to November 23, 2018show more dates >> Learn more and register >>
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 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, 2018show more dates >> Learn more and register >>
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 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, 2018show 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 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, 2018show more dates >> Learn more and register >>
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:August 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, 2018show more dates >> Learn more and register >>
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 03, 2017 to March 03, 2017June 09, 2017 to July 07, 2017February 02, 2018 to March 02, 2018June 08, 2018 to July 06, 2018show more dates >> Learn more and register >>
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 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, 2018show more dates >> Learn more and register >>
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:November 18, 2016 to December 16, 2016May 26, 2017 to June 23, 2017show more dates >> Learn more and register >>
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:April 14, 2017 to May 12, 2017April 13, 2018 to May 11, 2018April 12, 2019 to May 10, 2019show 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 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, 2018show 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 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, 2018show 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 16, 2016 to October 14, 2016September 15, 2017 to October 13, 2017September 14, 2018 to October 12, 2018show 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 13, 2017 to February 10, 2017May 19, 2017 to June 16, 2017January 05, 2018 to February 02, 2018May 18, 2018 to June 15, 2018show more dates >> Learn more and register >>
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, 2018show more dates >> Learn more and register >>
Social Data Mining With Python
Tuition: $469 (5.0 CEUs) Next three dates:October 21, 2016 to November 18, 2016May 26, 2017 to June 23, 2017October 20, 2017 to November 10, 2017May 25, 2018 to June 22, 2018October 19, 2018 to November 16, 2018show 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 27, 2017 to February 24, 2017January 26, 2018 to February 23, 2018January 25, 2019 to February 22, 2019show 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 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, 2018show more dates >> Learn more and register >>
Tuition and Fees: $5,642
The above "pay-as-you-go" estimate includes the application fee, the registration fee, and individual course fees that you pay as you progress through the program. Considerable savings are available if you pay the program cost upon enrollment, or in installments:
- Pay for your program upon enrollment: $5000
- Pay in 18 monthly installments: $290/month
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 $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!
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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