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EL ENG X480.1 - Programming With R

40986
Get an introduction to the R programming language in order to perform data manipulation, statistical analysis and graphics applications. Thousands of libraries or packages are available for everything from time-series analysis and machine learning to data visualization. As a result, R is rapidly becoming the language of choice for engineers, scientists, researchers and business analysts who engage in data preparation and analysis to generate high-quality typographical and graphical results.

Course Outline

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Course Objectives

  • Install and configure R and essential R development tools, write R programs, and run them to generate tabular and graphical results.
  • Use R to create, or read-in external datasets, storing data in all of the commonly used R data structures (vectors, matrices, arrays, data frames, factors and lists).
  • Manage and manipulate data; perform data type conversions; merge data sets; deal with missing values; and extract, delete, or transform subsets of data based on logical criteria.
  • Use basic R language constructs such as variables, branching and looping statements, write and call programmer defined, built-in and externally installed (package) functions.
  • Employ R to perform basic data analysis using data exploration, statistical analysis and machine-learning techniques.

What You Learn

  • Writing and running R programs
  • Creating datasets
  • R language elements
  • R functions
  • Basic graphs; bar plots, pie charts, histograms, density, box and dot plots
  • Descriptive statistics
  • Correlation and hypothesis testing; regression, variance
  • Advanced graphing
  • Statistical modeling: linear models, regression, classification trees

How You Learn

  • Lectures
  • In-class exercises
  • Online discussion boards
  • In-class exams

Is This Course Right for You?

If you want to learn the fundamentals of the R programming language and gain a solid foundation for future study, then this course is geared to your needs. Also, those who want to learn R to perform data exploration and analysis using statistical and machine learning techniques should enroll. Scientists, engineers, business analysts and social science researchers who explore and analyze data, and wish to present their results in well-formatted textual or graphical forms will find this course a fit.

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Sections

Thank you for your interest in this course. Unfortunately, the course you have selected is currently not open for enrollment. Please contact the academic department at the email or phone number listed in the Notes section for more information.

This course applies to the following programs:

Advanced Program in Software Development

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Programming Courses

  • Java: Discovering Its Power
  • Mastering Python
  • UNIX/Linux System Administration Programming: Shell, C and Perl
  • C++ Programming
  • Data Structures and Algorithms

Data and Databases Courses

  • Machine Learning and Deep Learning With Spark
  • Practical Machine Learning (With R)
  • Programming With R
  • Python for Data Analysis and Scientific Computing
  • SQL Database Programming

Learn More About this Program

Certificate Program in Data Science

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Programming

  • Programming With R
  • Python for Data Analysis and Scientific Computing
  • Introduction to Data Science

Machine Learning

  • Introduction to Machine Learning Using Python
  • Machine Learning and Deep Learning With Spark
  • Practical Machine Learning (With R)
  • Machine Learning With TensorFlow

Core Courses

  • Data Science Principles and Practice Using R
  • Practical Statistics for Data Scientists Using R
  • Introduction to Big Data
  • Data Science Principles and Practice Using Python

Electives

  • Introduction to Databases
  • Introduction to SQL

Learn More About this Program

Professional Program in Data Analysis

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Data Analysis Courses

  • Introduction to Data Analytics
  • Programming With R
  • Python for Data Analysis and Scientific Computing
  • Data Analytics and Visualization
  • Practical Statistics for Data Scientists Using R

SAS Analytics Courses

  • Introduction to the SAS System
  • Data Analysis Using the SAS System
  • Predictive Analytics Using the SAS System

Data Management Courses

  • Introduction to Databases
  • Introduction to SQL
  • Business Intelligence With SQL Server
  • Data Mining Using SQL

Learn More About this Program

Notes

Departmental contact: extension-techeng@berkeley.edu | (510) 642-4151

Prerequisites

To be successful in this course, it is strongly recommended to have the following knowledge, skills and abilities before you enroll:

  • Knowledge of statistics as covered in a first semester undergraduate course. Need to fulfill this prereq? Take a course in:
    • Introduction to Statistics STAT X10
       
  • Ability to program in at least one high-level programming language such as Python, Java, Ruby, JavaScript, C or C++. Need to fulfill this prereq? Take a course in:
    • Introduction to Computers and Programming COMPSCI X444.4
    • Python Programming EL ENG X442.3
    • First Course in Java EL ENG X429.9
    • JavaScript and jQuery: An Introduction COMPSCI X452.1
    • Introduction to C Language Programming EL ENG X24
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