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Data Science with R: Data Analysis and Visualization

  • Beginner
  • 15 and older
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  • 500 8th Ave, New York, NY
  • 35 hours over 5 sessions

Start Dates (0) $2,080.50/person

  • No class on Nov 9th & Nov 30th

No upcoming dates are currently available.

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Class Description

Description

This course is a 35-hour program designed to provide a comprehensive introduction to R for Data Analysis and Visualization. You’ll learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models with data. In addition to a theoretical framework in which to understand the process of data analysis, this course focuses on the practical tools needed in data analysis and visualization. By the end of the course, you will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting your codes.

Prerequisites
  • Basic knowledge about computer components
  • Basic knowledge about programming
Certificate
  • Certificates are awarded at the end of the program at the satisfactory completion of the course.
Syllabus

Unit 1: Basic Programming with R

Introduction to R
  • What is R?
  • Why R?
  • How to learn R
  • RStudio, packages, and the workspace
Basic R language elements
  • Data object types
  • Local data import/export
  • Introducing functions and control statements
In-depth study of data objects
Functions
Functional Programming

Unit 2: Basic Data Elements

Data transformation
  • Reshape
  • Split
  • Combine
Character manipulation
String manipulation
Dates and timestamps
Web data capture
API data sources
Connecting to an external database


Unit 3: Manipulating Data with “dplyr”
  • Subset, transform, and reorder datasets
  • Join datasets
  • Groupwise operations on datasets
Unit 4: Data Graphics and Data Visualization

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

Unit 5: Advanced Visualization

Customized graphics with ggplot2
  • Titles
  • Coordinate systems
  • Scales
  • Themes
  • Axis labels
  • Legends
Other plotting cases
  • Violin Plots
  • Pie charts
  • Mosaic plots
  • Hierarchical tree diagrams
  • scatter plots with multidimensional data
  • Time-series visualizations
  • Maps
  • R and interactive visualizations
Final Project
  • After 35 hours of structured lectures, students are encouraged to work on an exploratory data analysis project based on their own interests. A project presentation demo will be arranged afterwards.
Recommended Readings
  • R in a Nutshell, by Joseph Adler
  • R Graphics Cookbook: http://www.cookbook-r.com/Graphs/
  • Data Manipulation with R, by Phil Spector

Remote Learning

This course is available for "remote" learning and will be available to anyone with access to an internet device with a microphone (this includes most models of computers, tablets). Classes will take place with a "Live" instructor at the date/times listed below.

Upon registration, the instructor will send along additional information about how to log-on and participate in the class.

School Notes: We offer a certification licensed by the NYS Board of Education.

Refund Policy

Any student wishing to withdraw from a program must notify CourseHorse in writing. The date of withdrawal for refund purposes is the last date of physical attendance. The failure of a student to notify us in writing of withdrawal may delay refund of tuition due pursuant to Section 5001 and 5002 of the Education Law.

Any student requesting cancellation within seven days after signing the Enrollment Agreement but before instruction begins will be refunded all money paid less 5% cancellation fee. Thereafter, in the event of cancellation or termination by the school, refunds will be prorated based on the student's last date of attendance.

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NYC Data Science Academy

NYC Data Science Academy offers hands-on projects and real-world applications to teach students the skills needed for a career in data science. By enrolling, students become part of a supportive network that includes the NYC Open Data Meetup.

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