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.

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.

Preparing for Class

Onsite: Course Setup

What people say about our training

Great learning experience for me! Excellent instructor! I'm excited about applying this technology at my company!

Casey Murrell

TTI Inc.

This class exceeded my expectations. The instructor was excellent. He was knowledgeable and a great communicator (with a very clear, terrific voice which was a big plus for online classes). This was my first online class and I enjoyed it more than expected.

Sophie Wong

Legislative Data Center

Webucator provided a well run course with professional trainers. The course will allow our teams to track projects in much greater detail than before to continue to enhance the performance of our program teams.

Kevin McGrogan

BorgWarner

This class was great, and the ability to take it from home was the cherry on the sundae. It was intensive with lots of practice, rather than just reading and taking notes.

Walter Humfeld

Boeing

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Registered Education Provider (R.E.P.)

GSA schedule pricing

61,011

Students who have taken Instructor-led Training

11,714

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

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What people say about our training