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Data Science with R: Data Analysis and Visualization

Data Science with R: Data Analysis and Visualization

Overview

NYC Data Science Academy
500 8th Ave
Ste 905
New York, NY 10018
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Saturday, September 8, 2018 -
10:00am to 5:00pm
$2,190

Details

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

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