Data Analytics with R Training

Name: Data Analytics with R Training
Rating: 4.5 (7 reviews)

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.

Location

Public Classes: Delivered live online via WebEx and guaranteed to run . Join from anywhere!

Private Classes: Delivered at your offices , or any other location of your choice.

Goals

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.

Outline

Day One: Language Basics
1. Course Introduction
2. About Data Science
  1. Data Science Definition
  2. Process of Doing Data Science
3. Introducing R Language
4. Variables and Types
5. Control Structures (Loops / Conditionals)
6. R Scalars, Vectors, and Matrices
  1. Defining R Vectors
  2. Matricies
7. String and Text Manipulation
  1. Character Data Type
  2. File IO
8. Lists
9. Functions
  1. Introducing Functions
  2. Closures
  3. lapply/sapply Functions
10. DataFrames
11. Labs for All Sections
Day Two: Intermediate R Programming
1. DataFrames and File I/O
2. Reading Data from Files
3. Data Preparation
4. Built-in Datasets
5. Visualization
  1. Graphics Package
  2. plot() / barplot() / hist() / boxplot() / scatter plot
  3. Heat Map
  4. ggplot2 Package ( qplot(), ggplot())
6. Exploration with Dplyr
7. Labs for All Sections
Day 3: Advanced Programming With R
1. Statistical Modeling With R
  1. Statistical Functions
  2. Dealing with NA
  3. Distributions (Binomial, Poisson, Normal)
2. Regression
  1. Introducing Linear Regressions
3. Recommendations
4. Text Processing (tm package / Wordclouds)
5. Clustering
  1. Introduction to Clustering
  2. KMeans
6. Classification
  1. Introduction to Classification
  2. Naive Bayes
  3. Decision Trees
  4. Training Using Caret Package
7. Evaluating Algorithms
8. R and Big Data
  1. Hadoop
  2. Big Data Ecosystem
  3. RHadoop
9. Labs for All Sections

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.

What people say about our training

Great customer service putting the student first and highly knowledgeable instructors. They even ran the class with one student which was amazingly helpful to me.

Gail Valenti

Cambridge Health Alliance

The class moved at a good pace and the instructor kept us all involved.

Jerry Beasler

Penford

My Instructor was very knowledgeable and helpful and went above and beyond to help find solutions to a technical issue I had. Overall an excellent experience and I will be a returning client!

Terri Manning

Sykes Assistance Services

I very much enjoyed my Excel 3 class. I learned a lot, and will recommend this to other members of my company as I thought it was very informative and a much better use of time and money than many live in-person Microsoft Suite classes that I have attended.

Elyse Castillo

Entertainment Cruises

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Registered Education Provider (R.E.P.)

GSA schedule pricing

63,451

Students who have taken Instructor-led Training

11,895

Organizations who trust Webucator for their Instructor-led training needs

100%

Satisfaction guarantee and retake option

9.21

Students rated our Data Analytics with R Training trainers 9.21 out of 10 based on 7 reviews

Data Analytics with R Training

Training for your Team

What people say about our training