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Instructor is Claire Tu (Graduate of Data Science Bootcamp & University of North Carolina at Chapel Hill).
Sat, Sep 10, 2016 @ 10:00 AM   $2190   NYC Data Science Academy, 500 8th Ave, Ste 905
 
     
 
 
              

  
 
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LOCATION
EVENT DETAILS
This intensive Data Science with R Beginner Level course being offered by NYC Data Science Academy is a five week course that 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.Why R is important: R is a powerful, comprehensive, and dynamic

Course Time: 10am to 5 pm

Instructor
Claire Tu Instructor at NYC Data Science Academy. Claire is a graduate of the Data Science Bootcamp and has joined the Academy to leverage her data science skills. As a quantitative analyst who previously worked at non-profit organizations and research institutes in Beijing, New York and North Carolina, she has a keen interest in deploying quantitative methods and visualization tools to solve problems. Claire graduated from the University of North Carolina at Chapel Hill where she studied urban policy and planning. She loves tackling interesting data problems from social and geographic aspects.

Syllabus
Each class is 27 hours of classroom guidance with an optional three week-long showcase project of students own choices and optional presentation of their projects. This intensive class will introduce you to the wonderful world of R and provide you with an excellent understanding of the language that leaves you with a firm foundation to build upon. From the rudimentary building blocks of programming basics, to data manipulation and use of advanced drawing packages, the course will conclude with a demonstration of a project of your choice on Project Demo Day. For Demo Day you will access and analyze real data, utilizing the tools and skill set taught to you throughout the course.Upon 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.

1. Introduction to R 3 hours
Abstract: Students will learn the fundamental characteristics of the R language, and acquire essential programming skills to apply to future techniques in data handling, analysis, and visualization.
Outline:
What is R?
Why R?
How to get help
R language resources
Installing and using packages
Workspace

2. Programming with R 12 hours
Abstract: This session teaches how to manipulate data and use R for all kinds of data conversion and restructuring processes that are frequently encountered in the initial stages of data analysis. We will cover many powerful data manipulating packages such as dplyr and reshape2. We will also cover string processing operations and advanced data capture such as web scraping, API usage, and external database connections.

Outline:
Data Objects: Vectors, Matrices, Data Frames, and Lists
Local data import/export
Functions
Control Statements
Data sorting
Merging Data
Remodeling Data
String Manipulation
Dates and time stamps
Web data capture
API data sources
Connecting to an external database
Manipulating data with dplyr

3. Data Graphics and Data Visualization 6 hours
Abstract: We will cover some basic plotting types and two advanced drawing packages (lattice and ggplot2). Throughout the lectures we will focus on using ggplot2 scheme to develop an understanding of the fundamental data visualization processes and to explore the various options of describing and examining data.
Outline:
Core ideas of data graphics and data visualization
R graphics engines
o Base
o Grid
o Lattice
o ggplot2
Big data graphics with ggplot2

4. Advanced Visualization 6 hours
Abstract:This session will cover many customized visualization functions in ggplot2. We will also explore many of the advanced visualization packages to deal with different datasets (e.g. time series data, geographic data, real-time data).

Outline:
Customized graphics with ggplot2
Titles
Coordinate systems
Scales
Themes
Axis labels
Legends

Other plotting cases
o Violin Plots
o Pie charts
o Mosaic plots
o Hierarchical tree diagrams
o scatter plots with multidimensional data
o Time-series visualizations
o Maps
o R and interactive visualizations

Intended Audience and Prerequisite
Are you interested in better understanding your data, and not so interested in mastering a programming language? Have you tried learning R from a book or website, but have been discouraged? If so, this is the course for you.We assume that youve never programmed before (although some experience doesnt hurt), and we teach you the best tools to help analyze your data. You wont be a master programmer by the end of this two-day course, but through immersion you will have learned the basics of Rs syntax and grammar, and youll have started building an effective R vocabulary for visualizing, transforming, and modeling data.
 
 
 
 
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