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With Paul Trowbridge (Adjunct faculty @ NYU & Instructor @ NYC Data Science Academy).
Sat, Jun 06, 2015 @ 10:00 AM   $2190   NYC Data Science Academy, 205 E 42nd St
 
     
 
 
              

      
 
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LOCATION
EVENT DETAILS
Details
Date: Saturday |
Jun 6, 13, 27, July 11, 18
Time:
10am to 5 pm
Venue:
205 E 42nd Street, 16th Floor, New York, NY 10017 (5 min from Grand Central)
Online course option:
Students can take it remotely through recorded youtube sessions with google hangout TA support, email info@nycdatascience.com to get enrolled
For corporate training or small group training inquiry:
Email info@nycdatascience.com to get corporate/group discount
Instructor
Paul Trowbridge, Instructor at NYC Data Science Academy. He is a adjunct faculty at NYU, where he teaches data visualization and an instructor for the New York City Data Science Academy. Paul Trowbridge is also a Ph.D. candidate in statistics at Rutgers University. Paul has worked on projects in fMRI brain imaging studies, the analysis of international dispute data, experimental psychology, micro-simulation methods in urban planning and urban economics applications, and the epidemiology of Chlamydia.
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 - 10 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 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
3. Principal Statistical Methods - 7 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 also cover string processing operations and advanced data capture such as web scraping, API usage, and external database connections.

Outline:

Descriptive Statistics
Hypothesis testing
Linear Regression
Logistic Regression
Introducing non-parametric statistics
4. Data Graphics and Data Visualization - 7 hours
Abstract: We will quickly cover basic plotting types before introducing two advanced drawing packages (lattice and ggplot2), using the two graphing schemes to develop an understanding of the fundamental processes behind data visualization and the various options available to the data scientist to describe her data through clear and beautiful visualizations.

Outline:

Core ideas of data graphics and data visualization
R graphics engines
Base
Grid
Lattice
ggplot2
Modern data graphics with ggplot2

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 you've never programmed before (although some experience doesn't hurt), and we teach you the best tools to help analyze your data. You won't be a master programmer by the end of this two-day course, but through immersion you will have learned the basics of R's syntax and grammar, and you'll have started building an effective R vocabulary for visualizing, transforming, and modeling data.
 
 
 
 
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