
Data Analytics with R Training
Course Length:
Delivery Methods:
Course Topics
- Learn the language basic of R.
- Work with loops and conditionals.
- Work with built-in datasets.
- Work with visualization.
- Work with statstical modeling with R.
- Work with clustering and classification.
- Learn about R and big data.
Course Overview
R is a very popular, open source environment for statistical computing, data analytics and graphics. This Data Analytics with R Training class introduces R programming language to students. It covers language fundamentals, libraries, and advanced concepts and advanced data analytics and graphing with real world data.
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 3: 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
- Hadoop
- Big Data Ecosystem
- RHadoop
- Labs for All Sections
- Statistical Modeling With R
Class Materials
Each student in our Live Online and our Onsite classes receives a comprehensive set of materials, including course notes and all the class examples.
Class Prerequisites
Experience in the following is required for this R Programming class:
- Basic programming background.
Request a Private Class
- Private Class for your Team
- Online or On-location
- Customizable
- Expert Instructors