Data Science Certification Training – R Programming

Name: Data Science Certification Training - R Programming
SKU: 2217
Price: 15000.00 INR
Availability: InStock

Category:

Certification Courses/ Combo Courses/ Corporate Training/ Data Analytics/ Programming Languages/ Short Term Courses/

~~20,000.00₹~~ 15,000.00₹

Price ~~20,000.00₹~~ 15,000.00₹

Duration: 2.5 months

Lectures: Yes

Video: Yes

Yes

Become an expert in the various data analytics techniques using R. Master the data exploration, data visualization, predictive analytics, and descriptive analytics techniques. Get hands-on practice on R by implementing various real-life, industry-based projects in the domains of healthcare, retail, insurance, finance, airlines, music Industry, and on unemployment. The course is best suited for beginners as well as experienced professionals who want to use R for data analytics.

Course description

What’s the focus of this course?

The Data Science with R training course has been designed to impart an in-depth knowledge of the various data analytics techniques which can be performed using R. The course is packed with real-life projects, case studies

Mastering advanced statistical concepts: The course also includes the various statistical concepts like linear and logistic regression, cluster analysis, and forecasting. You will also learn hypothesis testing.

As a part of the course, you will be required to execute real-life projects using CloudLab. The compulsory projects are spread over four case studies in the domains of healthcare, retail, and Internet. R CloudLab has been provided to ensure a practical and hands-on experience. Additionally, we have four more projects for further practice.
What are the course objectives?
This course will enable you to:
- Gain a foundational understanding of business analytics
- Install R, R-studio, and workspace setup. You will also learn about the various R packages
- Master the R programming and understand how various statements are executed in R
- Gain an in-depth understanding of data structure used in R and learn to import/export data in R
- Define, understand and use the various apply functions and DPLYP functions
- Understand and use the various graphics in R for data visualization
- Gain a basic understanding of the various statistical concepts
- Understand and use hypothesis testing method to drive business decisions
- Understand and use linear, non-linear regression models, and classification techniques for data analysis
- Learn and use the various association rules and Apriori algorithm
- Learn and use clustering methods including K-means, DBSCAN, and hierarchical clustering
Who should take this course?
There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals:
- IT professionals looking for a career switch into data science and analytics
- Software developers looking for a career switch into data science and analytics
- Professionals working in data and business analytics
- Graduates looking to build a career in analytics and data science
- Anyone with a genuine interest in the data science field
- Experienced professionals who would like to harness data science in their fields
Prerequisites: There are no prerequisites for this course. If you are new in the field of data science, this is the best course to start with.
What is CloudLab?

CloudLab is a cloud-based R lab offered along with the course to ensure a hassle-free execution of the project work included.

With CloudLab, you do not need to install and maintain R on a virtual machine. Instead, you’ll be able to access a preconfigured environment—on CloudLab via your browser.

You can access CloudLab from the Simplilearn LMS (Learning Management System) for the duration of the course.
Course Description

Introduction to Business Analytics

Types of Analytics

Case study

Data Science and its importance

Introduction to R

Installing R

Installing R Studio

Workspace Setup

R Packages

R Programming

if statements

for statements

while statements

repeat statements

break and next statements

switch statement

scan statement

Executing the commands in a File

R Data Structure

Data structures

Vector

Matrix

Array

Data frame

List

Factors

Apply Functions

DPLYR & apply Function

Import Data File

DPLYP – Selection

DPLYP – Filter

DPLYP – Arrange

DPLYP – Mutate

DPLYP – Summarize

Data Visualization

Data visualization in R

Bar chart, Dot plot

Scatter plot, Pie chart

Histogram and Box plot

Heat Maps

World Cloud

Introduction to Statistics

Type of Data

Distance Measures (Similarity, dissimilarity, correlation)

Euclidean space.

Manhattan

Minkowski

Cosine similarity

Mahalanobis distance

Pearson’s correlation coefficient

Probability Distributions

Hypothesis Testing I

Hypothesis Testing – T Test, Anova

Hypothesis Testing II

Hypothesis Testing about population

Chi Square Test

F distribution and F ratio

Regression Analysis

Linear Regression Models

Non Linear Regression Models Lesson

Classification

Decision Tree

Logistic Regression

Bayesian

Support Vector Machines

Clustering

K-means Clustering and Case Study

DBSCAN Clustering and Case study

Hierarchical Clustering

Association

Apriori Algorithm

Candidate Generation

Visualization on Associated Rules

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