Data Science with R

Master the skill to transform data to intelligent and meaningful information and insights. Learning data science with R plays an important role in getting your dream job in the field of data science. Enrol for this course now to understand the core programming concepts of R language, and how it can be used in the field of Data Science.

Content Provider

iNURTURE

Course Level

Intermediate

Mode Of Delivery

Self-Paced

Duration

40 hrs

Certification By

iNURTURE

Course Validity

Valid for 6 months post activation

Learning Resources

Videos, Easy Accessibility

Industry

Information Technology

Course Fee

This is a paid course.

Enroll Now

~~1,800/-~~ 1599/-

Description

R is a programming language and software environment for statistical analysis, graphics representation and reporting is a programming language and environment commonly used in statistical computing, and data analytics and scientific research.R allows us to integrate with other languages (C, C++). Thus, you can easily interact with many data sources and statistical packages. As a result, R programming language has large growing community of users.

This Course

With this course, you will easily understand the core programming concepts of R language. This course also helps you acquire a thorough knowledge about looping and condition statements in R programming.

Learning Outcomes:

By the end of this course, you will be able to:

Understand the core programming concepts of R language.

Know the Looping and condition statements in R Programming

Identify different options in I/O operations in R programming.

Understand the importance of statistical functions in R programming language

Understand the basic concepts of integrating other object oriented programming with R.

Curriculum

Module 1: Advance Time Series Modelling

Box - Jenkins Methodology

Introduction to Auto Regression and Moving Averages, ACF, PACF, Detecting order of ARIMA processes

Seasonal ARIMA Models (P,D,Q)(p,d,q)

Introduction to Multivariate Time series Analysis

Using built in R datasets

Module 2: Stock market prediction

Live example/ live project

Using client given stock prices/taking stock price data

Module 3: Pharmaceuticals

Case Study with the Data

Based on open set data

Module 4: Market Research

Case Study with the Data

Based on open set data

Module 5: Machine Learning

Supervised Learning Techniques

Conceptual Overview

Module 6: Machine Learning

Unsupervised Learning Techniques

Association Rule Mining Segmentation

Conceptual Overview

Module 7: Fraud Analytics

Fraud Identification Process in Parts procuring

Sample data from online

Module 8: Text Analytics

Text Analytics

Sample text from online

Module 9: Social Media Analytics

Social Media Analytics

Sample text from online

Key Features

8 well-structured Modules

12 Videos

Certificate of Completion

Career Opportunities

Students can fetch the following job opportunities after attending this course

Data Scientist

Web Analytics Manager, Data Strategy & Insights

Associate Data Scientist

Quantitative Analytics Associate

System Engineer

Certification

After completing this course and successfully passing the certification examination, the student will be awarded the “Data Science with R” certification.

If a learner chooses not to take up the examination, they will still get a 'Participation Certificate'.

Who Should Attend

Engineering and IT students

Graduates with a programming background

Frequently Asked Questions

Where can I find courses on the Platform?

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