Data Science with R Training

Live Online & Classroom Enterprise Training

Data science, also known as data-driven science, is an interdisciplinary field about scientific processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured. This course makes you familiar with extracting, analyzing & interpreting data.

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Enterprise Reporting
Lifetime Access
CloudLabs
24x7 Support
Real-time code analysis and feedback

What is Data Science with R Training about?

R is a powerful language used widely for data analysis and statistical computing. In this course, you will be able to learn data science using R. By the end of this course, you will have good exposure to building predictive models using machine learning on your own.

Key Features:

Cloud labs
24/7 Support
Access to recordings and materials
Lesson-end quizzes
Course-end Assessments
Hands-on assignment

What are the objectives of Data Science with R Training ?

At the end of Data Science with R training, you will be able to:

Explain the concept of Business Decisions and Analytics
Understand the R Programming
Describe Data Structures
Discuss Data Visualization
Understand Statistics
Explain the Regression Analysis
Describe Classification
Explain Clustering
Understand Association

Who is Data Science with R Training for?

Those with passion for Data Science, Data Analysts, Software Engineers and bachelor degree holders looking to grow in their career

What are the prerequisites for Data Science with R Training?

Some knowledge of programming and statistics

Available Training Modes

Live Online Training

18 Days

Classroom Training

3 Days

Self-Paced Training

7 Hours

Course Outline Expand All

Expand All

Business Decisions and Analytics

Business Decisions

Business Analysis

Types of Analytics

Applications of Business Analytics

Introduction to R Programming

R for Data Analytics

Steps to perform Data Analysis in R

Basic Syntax in R

Data Types and Variables

Operators

Conditional Statements

Loops

Loop Control Statements

Functions

Components of a Function

Built-in Functions

Data Structures

Steps for working with data

Identifying Data Structures

Assigning values to Data Structures

Manipulating Data

Data Visualization

Introduction

Graphics used for Data Visualization

ggplot2

File formats of graphic outputs

Statistics Essentials - I

What is Hypothesis?

Types of Hypothesis

Types of Data Sampling

Types of Errors

Confidence Level

Critical Region

Level of Significance

Statistics Essentials - II

Hypothesis Test

Types of Hypothesis Test

Hypothesis Test about population means

Hypothesis Test about population Variance

Hypothesis Test about population Proportions

Regression Analysis

What is Regression Analysis?

Types of Regression Models

Linear Regression

Non-linear Regression

Non-linear to Linear Models

Principle Component Analysis

Classification

What is Classification

Types of Classification

Logistic Regression

Support Vector Machines

K-Nearest Neighbors(KNN)

Naïve Bayes Classifier

Decision Trees

Random Forest Classification

Evaluating Classifier Models

Clustering Methods

Clustering and its applications

Clustering Methods

K-means Clustering

Hierarchical Clustering

Density-based Clustering

Association

Association Rules

Apriori Algorithm

Who is the instructor for this training?

The trainer for this Data Science with R Training has extensive experience in this domain, including years of experience training & mentoring professionals.

Reviews

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