NYC R Programming Classes – starting on July 13th, 2014 (this coming Sunday)

We are happy to announce our 6th offering R class at NYC in the past 10 months.  R community is booming. Learn Data Science at the heart of NYC with us!

You can sign up for our Sunday Intensive beginner level R classes at
NYC Data Science Academy (click to sign up) or email [email protected] for more info.

Brief: The course (which will meet five Sundays) will start from the basics,
introducing the building blocks used for programming in R and building
intuition for writing clean and robust code. We will move on to cover
data analysis, applications of statistical techniques, and graphing. This course will introduce you to the wonderful wold of R and provide you with an excellent understanding of the language that leaves you with a firm foundation to build upon.

Date: July 13th, 20th, 27th, and Aug 3rd and 10th(five Sundays)

Time: 10:00 am to 5:00 pm

Venue: 500 7th Ave, 17th Fl., New York, NY (close to Times Square)

Instructors:
Scott Kostyshak (Data Scientist @ Supstat Inc, 5th year PhD at Princeton Univ.)
Charlie Redmon (Project Manager @Supstat Inc, Master degree)

Cost:

* $1500/5 classes is highly recommended for absolute beginner or someone have little experience if you want to master the content and feel very comfortable to work with R from now on.

* $350/class if  you have good R programming skilss and want to enhance your skill on specific topics.

* For group(5+ persons) and enterprise pricing, please email [email protected]

Course Outline:
(Content may be adjusted based on the real teaching condition)

Why R is important
R is a free, full, and dynamic programming language that, since its release in 1996, is on course to eclipse traditional statistical packages as the dominant interface in computational statistics, visualization, and data science. As an open-source platform, R has grown to become an incredibly flexible tool that can be applied to nearly every graphical and statistical problem, at virtually no cost to the user. The community of R users is continuing to build new functionality.

Project Demo Day and Certificates

After the rudimentary building blocks of programming basics, to data manipulation and use of advanced drawing packages, the course ends with a demonstration of a project of your choice on Project Demo Day. On Demo Day you will access and analyze real data, utilizing the tools and skillsets taught to you throughout the course. After the successful completion of the course, you will qualify for one of three certificates: Extraordinary Standing, Honorable Graduation, and Active Participation. Certificates are awarded according to your understanding, skill, and participation.

Refund Policy:

Students may receive full tuition reimbursement upon completion of the first class day if they decided to drop.

Syllabus

1. Basics: 12 hours
Abstract: Explain the basic operation of knowledge through this unit of study. Students will learn the characteristics of R, resource acquisition mode, and mastery of basic programming.
Case Study and Exercises: Use the R language to complete certain Euler Project problems.

  • How to learn R
  • How to get help
  • R language resources and books
  • RStudio
  • Expansion Pack
  • Workspace
  • Custom Startup Items
  • Batch Mode
  • Data Objects
  • Custom Functions
  • Control Statements
  • Vectorized Operations

2. Getting Data: 6 hours
Abstract: Explain the various ways the R language reads data, bring the participants through basic knowledge of web crawling, and connect to the database via sql statement calling data from a variety of locally read excel file data.
Case and Exercises: Crawl watercress data on the site and write a custom function.

  • Web data capture
  • API data source
  • Connect to the database
  • Local Documentation
  • Other data sources
  • Data Export

3. Data Manipulation: 6 hours
Abstract: How to manipulate data and use R for the all kinds of data conversion, especially for string operation processing.
Case Study and Exercise: Find the QQ (the most used instant messenger tool) group, then discuss research options with text features.

  • Data sorting
  • Merge Data
  • Summary data
  • Remodeling Data
  • Take a subset of data
  • String manipulation
  • Date Actions

4. Data Visualization: 6 hours
Abstract: Cover two advanced drawing packages (Lattice and ggplot2) and understand the various methods of visualization.
Case and Exercises: Using graphics, text and other data.

  • Histogram
  • Point
  • Column
  • Line
  • Pie
  • Box Plot
  • Scatter
  • Matrix related
  • Map

What does SupStat offer?(click on the image to see more details.)
Our services include consulting on statistical methods, software training on statistical computing and data analysis (mainly R), statistical graphics and data visualization, as well as statistical reports. We have Beijing, Shanghai, and New York offices. Our team includes top 0.1% ranked Kagglers.(www.kaggle.com hosts excellent data mining competitions and gathers more than 100K data scientists.) For business inquiry, please email: [email protected].

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