Data Analytics With R 교육 과정

Course Code

dataar

Duration

21 hours (usually 3 days including breaks)

Requirements

  • Basic programming background is preferred

Setup

Overview

R 은 통계 컴퓨팅, 데이터 분석 및 그래픽을위한 매우 인기있는 개방형 소스 환경입니다. 이 과정은 학생들에게 R 프로그래밍 언어를 소개합니다. 언어 기초, 도서관 및 고급 개념을 다룹니다. 실제 데이터로 고급 데이터 분석 및 그래프 작성.

청중

개발자 / 데이터 분석

지속

3 일

체재

강의 및 실습

Machine Translated

Course Outline

Day One: Language Basics

  • Course Introduction
  • About Data Science
    • Data Science Definition
    • Process of Doing Data Science.
  • Introducing R Language
  • Variables and Types
  • Control Structures (Loops / Conditionals)
  • R Scalars, Vectors, and Matrices
    • Defining R Vectors
    • Matricies
  • String and Text Manipulation
    • Character data type
    • File IO
  • Lists
  • Functions
    • Introducing Functions
    • Closures
    • lapply/sapply functions
  • DataFrames
  • Labs for all sections

Day Two: Intermediate R Programming

  • DataFrames and File I/O
  • Reading data from files
  • Data Preparation
  • Built-in Datasets
  • Visualization
    • Graphics Package
    • plot() / barplot() / hist() / boxplot() / scatter plot
    • Heat Map
    • ggplot2 package (qplot(), ggplot())
  • Exploration With Dplyr
  • Labs for all sections

Day Three: Advanced Programming With R

  • Statistical Modeling With R
    • Statistical Functions
    • Dealing With NA
    • Distributions (Binomial, Poisson, Normal)
  • Regression
    • Introducing Linear Regressions
  • Recommendations
  • Text Processing (tm package / Wordclouds)
  • Clustering
    • Introduction to Clustering
    • KMeans
  • Classification
    • Introduction to Classification
    • Naive Bayes
    • Decision Trees
    • Training using caret package
    • Evaluating Algorithms
  • R and Big Data
    • Connecting R to databases
    • Big Data Ecosystem
  • Labs for all sections

회원 평가

★★★★★
★★★★★

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