AcademyR Course Catalog

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Courses Listed by Role

Data Analyst

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4

Data Scientist

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6

R Programmer

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9

Statistician

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10

BI Developer

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11

System Administrator

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12

Big Data Architect

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13

Courses Listed by Skill Level

Introductory Course Offerings

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15

Intermediate Course Offerings

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16

Advanced Course Offerings

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18

Revolution R Enterprise Certification

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19

Interactive Self-Paced Courses on DataCamp

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20

Contact Us

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21

Don’t see your learning needs listed here?

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available in classroom, virtual, self-paced, and blended learning formats .

Our Philosophy

We believe that active learning is more effective—and more fun—for every individual .

Through cooperative participation, we build on current knowledge with real-world

context to achieve your training goals .

AcademyR

Impact

Assessment

Real World

Contexts

Prior

Knowledge

Cooperation

Goal-Based

Curriculum

Active

Learning

Fun

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Data Analyst

Data analysts collect, explore, and visualize data to find valuable patterns .

When I first learned R, I found it very frustrating—but I

quickly realized that most of that frustration came from

expecting R to work like other stat packages. I wasn’t

alone! My online notes on how to avoid common pitfalls

soon got over 10,000 hits per month. That led to books

and workshops, and I now find it very rewarding to guide

people through the parts of R that are most likely to trip

them up.

Robert A. Muenchen is the author of the books R for SAS and SPSS

Users and, with Joseph M. Hilbe, R for Stata Users . He is also the creator

of r4stats.com, a popular website devoted to analyzing trends in analytics software and helping people learn the R language. Bob has more than 30 years of experience and is currently the manager of OIT Research Computing Support at the University of Tennessee. His workshops have drawn attendees from more than 500 organizations, and Bob has served on the advisory boards of SAS Institute, SPSS Inc., StatAce OOD, Intuitics, the Statistical Graphics Corporation, and PC Week Magazine .

Robert A. Muenchen

R Training Partner and Author

“

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Fundamentals of the R Language

Explore the basics of R programming, data manipulation, graphics, and data analysis .

Course: T-RRO-101 Level: Introductory

Prerequisite: Some programming and statistical skills Duration: 1 day

Introduction to

Revolution R Enterprise

Learn how Revolution R Enterprise addresses the biggest soft spot of R . From architectural overview to data management and transformations, all topics cover use of the Revolution R Enterprise ScaleR package . Specialized versions are available for supported data platforms .

Course: T-RRE-103 Level: Introductory

Prerequisite: T-RRO-101 or T-RRO-102 Duration: 1 day

Specializations for

Data Analysts

Introduction to R for SAS, SPSS,

or Stata Users

Get a foundation in R programming specifically for those familiar with statistical software such as SAS, SPSS, or Stata . Knowledge of basic data analysis concepts is assumed .

Course: T-RRO-102 Level: Introductory

Prerequisite: Some programming and statistical skills Duration: 2 days

Managing Data with R

Explore the most common data management tasks in R using built-in functions and the latest packages . Topics covered include methods for data import, export, munging, and manipulation .

Course: T-RRO-201 Level: Intermediate

Data Visualization in R

Learn how to build graphics in R using a range of packages, including base R, lattice, and ggplot2 .

Course: T-RRO-202 Level: Intermediate

Core Courses for

Data Analysts

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Data Scientist

Data scientists find and interpret rich data sources and manage large data sets despite hardware,

software, and bandwidth constraints . They present and communicate their insights and findings to

both technical and non-technical audiences .

T

he central Data Engineering & Analytics team

partnered with AcademyR to provide professional

development to our analytics professionals at

various levels—junior analysts, many with an SAS

background, and experienced analysts. Over 65

employees participated in these sessions, and the

feedback was highly positive. The R user community

within the company is growing, and employees feel

they, too, are growing!

Giovanni Seni, PhD, is an active data-mining practitioner in Silicon Valley with more than 15 years R&D experience in statistical pattern recognition and data- mining applications. He is the author of the book, Ensemble Methods in Data Mining: Improving Accuracy Through

Combining Predictions, an open source contributor (project REgo), and

an adjunct faculty member at the Computer Engineering Department of Santa Clara University.

Giovanni Seni

PhD, Experienced Senior Data Scientist & Data Science Team Lead

“

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Core Courses for

Data Scientists, Option 1

Predictive Modeling with

Revolution R Enterprise I

*

Survey algorithms and techniques that use R for predictive modeling and data mining, including linear regression, logistic regression, stepwise regression, GLM, and k-means clustering . Learn best practices in model evaluation and scoring .

Course: T-RRE-211 Level: Intermediate

Prerequisite: T-RRE-103 and Data Analyst curriculum Duration: 1 day

Predictive Modeling with

Revolution R Enterprise II

*

Survey algorithms and techniques that use R for predictive modeling and data mining, including decision trees, random decision forests, and boosted decision trees (popularly known as the ensemble methods) . Learn best practices in fine-tuning the models .

Course: T-RRE-212 Level: Intermediate

Core Courses for

Data Scientists, Option 2

Predictive Modeling with

Revolution R Open I

Survey algorithms and techniques that use R for predictive modeling and data mining, including linear regression, logistic regression, stepwise regression, GLM, and k-means clustering . Examine best practices in model evaluation and scoring .

Course: T-RRO-213 Level: Intermediate

Prerequisite: T-RRO-101 or T-RRO-102 and Data

Analyst curriculum

Duration: 1 day

Predictive Modeling with

Revolution R Open II

Survey algorithms and techniques that use R for predictive modeling and data mining, including decision trees, random decision forests, and boosted decision trees (popularly known as the ensemble methods) . Examine best practices in fine-tuning the models .

Course: T-RRO-214 Level: Intermediate

Prerequisite: T-RRO-213 and Data Analyst curriculum Duration: 1 day

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Specializations for

Data Scientists

Parallel Computing and

Simulations with

Explore techniques for parallel computing with R on computer clusters, multicore systems, or grid computing—and see how Revolution R Enterprise makes parallel computing easy .

Course: T-RRE-301 Level: Advanced

Maximizing R and Hadoop

Learn advanced MapReduce jobs in Hadoop using the RHadoop packages .

Course: T-RRP-311 Level: Advanced

Text Mining in R

Explore text analytics and natural language processing (NLP) in R, including structuring text and topic-modeling algorithms .

Course: T-RRO-321 Level: Advanced

Prerequisite: T-RRO-101 or T-RRO-102 and Data

Analyst curriculum

Duration: 2 days

Advanced R Programming

Topics include efficient programming and memory management, advanced function writing topics, simulation, environments, and object-oriented programming .

Course: T-RRO-351 Level: Advanced

Prerequisite: Practical experience in R; T-RRO-101

or T-RRO-102; and Data Analyst curriculum

Duration: 1 day

Building Your Own Algorithms

with RevoPemaR

™

Learn tools and techniques for writing parallel external memory algorithms in RevoPemaR to handle data exceeding computer memory . Specialized versions are available for supported data platforms .

Course: T-RRP-361 Level: Advanced

Prerequisite: T-RRO-351 and Data Analyst curriculum Duration: 1 day

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R Programmer

R programmers build applications for use by others who do not have R knowledge . They are proficient

in R language and its programming environment . Advanced practitioners improve the performance of

code written in R and build packages in R .

Courses for

R Programmers

Dynamic Reporting with R

Learn methods for creating reports—webpages (static and interactive), Microsoft Office documents (Word, Excel, PowerPoint), and publication-quality (LaTeX) reports—with R . Explore knitr, R Markdown, R2wd, R2PPT, googleVis, and Shiny .

Course: T-RRO-221 Level: Intermediate

Prerequisite: T-RRO-101 or T-RRO-102 and

Data Analyst curriculum

Duration: 2 days

Advanced R Programming

Course: T-RRO-351 Level: Advanced

Prerequisite: Practical experience in R; T-RRO-101 or

T-RRO-102; and Data Analyst curriculum

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Statistician

Statisticians collect, analyze, interpret, and present quantitative information . They design and manage

experiments and surveys, and they deal with the initial collection of data . Looking for patterns to help

make decisions, statisticians process and analyze the data in context . They also advise on findings and

recommend strategy .

Courses for

Statisticians

Statistics with

This course provides a survey of introductory statistics and hypothesis testing using Revolution R Enterprise . Topics covered include visualization, cross-tabulation, and linear regression, correlation, and clustering .

Course: T-RRE-111 Level: Introductory

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Courses for

BI Developers

Fundamentals of the R Language

Course: T-RRO-101 Level: Introductory

Developing Web Applications

with Revolution R Enterprise

Deploy R applications on a server for access by client applications through a web services API .

Course: T-RRE-241 Level: Intermediate

BI Developer

Business intelligence developers build analytical applications using technologies such as

Java/JavaScript/ .NET/PHP in the presentation layer and R in the analytics layer . They are

also familiar with SOA/REST protocols .

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System Administrator

System administrators oversee several corporate enterprise systems, including

Revolution R Open/Enterprise .

My favorite part of training others in R is

the personal interactions. I love it when

someone poses an everyday work problem

and I can help them solve it.

Jeremy Reynolds holds a PhD in Psychology and was a tenure-track faculty member researching the neural and computational mechanisms underlying learning, memory, and decision making. Jeremy started using R as a first-year graduate student in 2000 and now has more than 14 years of experience using R to manipulate, analyze, and visualize data (and of course evangelizing and teaching R).

Jeremy Reynolds

Senior Trainer, Revolution Analytics

“

Courses for

System Administrators

Explore the basics of R programming, data

manipulation, graphics, and data analysis .

Course: T-RRO-101 Level: Introductory

System Administration Training

*

This covers hands-on training for system administrators and others responsible for managing Revolution R Enterprise in production or development environments .

Course: T-RRE-231 Level: Intermediate

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Big Data Architect

Big data architects describe the structure and behavior of big data solutions and how they can be

delivered using technology like Hadoop . They define IT system architectures to support particular

business strategies and bring cross-functional, interdisciplinary knowledge to the team .

While at graduate school, I discovered R. The power of R

was captivating, but the learning curve was challenging.

My passion is to flatten the learning curve as much as

possible. I combine my expertise in computer science,

cognitive science, and statistics to facilitate learning.

Jamie Olson has BA in Computer Science and Cognitive Science and an MS in Computer Science. He has nearly a decade of experience in R, advanced statistical modeling, machine learning, and modeling complex systems.

Jamie Olson

Analytics Architect, Revolution Analytics

“

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Core Courses for

Big Data Architects

Course: T-RRO-101 Level: Introductory

Prerequisite: Some programming and statistical

skills; prior experience and training in complementary big data technologies

Duration: 1 day

Introduction to

Learn how Revolution R Enterprise addresses the biggest soft spot of R . From architectual overview to data management and transformations, all topics cover use of the Revolution R Enterprise ScaleR package . Specialized versions are available for supported data platforms .

Course: T-RRE-103 Level: Introductory

Prerequisite: T-RRO-101 or T-RRO-102; prior

experience and training in complementary big data technologies

Duration: 1 day

Developing Web Applications

Course: T-RRE-241 Level: Intermediate

Specializations for

Big Data Architects

Parallel Computing and

Simulations with

Explore techniques for parallel computing with R on computer clusters, multicore systems, or grid computing—and see how Revolution R Enterprise makes parallel computing easy .

Course: T-RRE-301 Level: Advanced

Prerequisite: T-RRE-211; prior experience and

training in complementary big data technologies

Duration: 1 day

Maximizing R and Hadoop

Course: T-RRP-311 Level: Advanced

Prerequisite: T-RRE-212; prior experience and

training in complementary big data technologies

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Course: T-RRO-101

Fundamentals of the R Language

Level: Introductory

Recommended for: Data Analysts | BI Developers

System Administrators | Big Data Architects

Introduction to R for SAS, SPSS,

or Stata Users

Get a foundation in R programming specifically for those familiar with statistical software such as SAS, SPSS, or Stata . Knowledge of basic data analysis concepts is assumed .

Level: Introductory

Prerequisite: Some programming and statistical skills Duration: 2 days

Recommended for: Data Analysts Course: T-RRE-103

Introduction to

Learn how Revolution R Enterprise addresses the biggest soft spot of R . From architectural overview to data management and transformations, all topics cover use of the Revolution R Enterprise ScaleR package . Specialized versions are available for supported data platforms .

Level: Introductory

Prerequisite: T-RRO-101 or T-RRO-102

Duration: 1 day

Recommended for: Data Analysts | Big Data Architects

Course: T-RRE-111

Statistics with

This course provides a survey of introductory statistics and hypothesis testing using Revolution R Enterprise .

Topics covered include visualization, cross-tabulation, and linear regression, correlation, and clustering .

Level: Introductory Prerequisite: T-RRE-103

Duration: 1 day

Recommended for: Statisticians

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Managing Data with R

Explore the most common data-management tasks in R using built-in functions and the latest packages . Topics covered include methods for data import, export, munging, and manipulation .

Level: Intermediate

Duration: 1 day

Recommended for: Data Analysts Course: T-RRO-202

Data Visualization in R

Learn how to build graphics in R using a range of packages, including base R, lattice, and ggplot2 .

Duration: 1 day

Recommended for: Data Analysts Course: T-RRE-211

Predictive Modeling with

Revolution R Enterprise I

Survey algorithms and techniques that use R for predictive modeling and data mining, including linear regression, logistic regression, stepwise regression, GLM, and

k-means clustering . Learn best practices in model

evaluation and scoring . Specialized versions are available for supported data platforms

Prerequisite: T-RRE-103

Duration: 1 day

Predictive Modeling with

Revolution R Enterprise II

Survey algorithms and techniques that use R for predictive modeling and data mining, including decision trees, random decision forests, and boosted decision trees (popularly known as the ensemble methods) . Learn best practices in fine-tuning the models . Specialized versions are available for supported data platforms .

Duration: 1 day

Recommended for: Data Scientists Course: T-RRO-213

Predictive Modeling with

Revolution R Open I

Survey algorithms and techniques that use R for predictive modeling and data mining, including linear regression, logistic regression, stepwise regression, GLM, and

k-means clustering . Examine best practices in model

evaluation and scoring .

Duration: 1 day

Recommended for: Data Scientists

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Predictive Modeling with

Revolution R Open II

Survey algorithms and techniques that use R for predictive modeling and data mining, including decision trees, random decision forests, and boosted decision trees (popularly known as the ensemble methods) . Examine best practices in fine-tuning the models .

Prerequisite: T-RRO-213

Duration: 1 day

Recommended for: Data Scientists Course: T-RRO-221

Dynamic Reporting with R

Learn methods for creating reports—webpages (static and interactive), Microsoft Office documents (Word, Excel, PowerPoint), and publication-quality (LaTeX) reports—with R . Explore knitr, R Markdown, R2wd, R2PPT, googleVis, and Shiny .

Duration: 2 days

Recommended for: R Programmers Course: T-RRE-231

System Administration Training

This covers hands-on training for system administrators and others responsible for managing Revolution R Enterprise in production or development environments . Specialized versions are available for supported data platforms .

Duration: 1 day

Recommended for: BI Developers | Big Data Architects

Developing Web Applications

Duration: 1 day

Recommended for: BI Developers | Big Data Architects

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Parallel Computing and

Simulations with

Explore techniques for parallel computing with R on computer clusters, multicore systems, or grid computing— and see how Revolution R Enterprise makes parallel computing easy .

Level: Advanced

Duration: 1 day

Recommended for: Data Scientists | Big Data Architects

Course: T-RRP-311

Maximizing R and Hadoop

Level: Advanced

Duration: 1 day

Recommended for: Data Scientists | Big Data Architects

Text Mining in R

Explore text analytics and natural language processing (NLP) in R, including structuring text and topic-modeling algorithms .

Level: Advanced

Duration: 2 days

Advanced R Programming

Level: Advanced

Prerequisite: T-RRO-101 or T-RRO-10 and practical experience in R

Duration: 1 day

Recommended for: Data Scientists | R Programmers

Course: T-RRP-361

Building Your Own Algorithms

with RevoPemaR

Learn tools and techniques in RevoPemaR for writing parallel external memory algorithms to handle data exceeding computer memory . Specialized versions are available in supported data platforms .

Level: Advanced

Prerequisite: T-RRO-351

Duration: 1 day

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Professional Revolution R Enterprise Certification is the industry’s first certification for advanced

big data analytics using Revolution R Enterprise—the big data, big analytics platform based on

the R statistical programming language . Experts forecast a huge talent gap within the advanced

analytics field in the coming years . At AcademyR, Revolution Analytics addresses this need for

advanced data-science skills by sharing our industry expertise . Revolution R Enterprise Certification

examinations may be scheduled as online or on-site proctored events .

Visit

revolutionanalytics.com/academyr-certification.

Revolution R Enterprise Certified Specialist

R is the most widely used statistical language today . The first choice of data scientists, it has

more than 2 million users worldwide . Offering scalable, high-performance enterprise analytics,

Revolution R Enterprise supports a variety of analytical capabilities, including exploratory data

analysis, model building, and model deployment .

Sucessful candidates must demonstrate their capabilities with Revolution R Enterprise for

advanced, industry-ready analytics projects . Topics covered in this examination include:

•

Introductory big data analytics

•

R as a programming language

•

Big data management in Revolution R Enterprise

•

Big data exploration and statistical analysis using Revolution R Enterprise

•

Advanced big data analytics: modeling in Revolution R Enterprise

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portal, tailored for hands-on experimentation in the browser . The platform uses in-browser coding

exercises powered by Revolution R Enterprise, supported by high-quality video and slide material

Visit

datacamp.com/tracks/revolution.

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www.academyr.com

[email protected]

Revolution Analytics

1-855-GET-REVO

2570 W. El Camino Real, Suite 222

Mountain View, CA 94040