R Data Mining Projects

This fast-paced video tutorial will help you solve predictive modeling problems using the most popular data mining algorithms through simple, practical cases. Practical and focused on real-world data mining cases, this course covers concepts such as spatial data mining, text mining, social media mining, and web mining.

  • Comprehensive training through 31 video sessions.
  • Make use of statistics and programming to understand data mining concepts and their application
  • Use R programming to apply statistical models to data
  • Get to know various data visualization libraries available in R to represent data
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Self-Paced

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Course Features

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About R Data Mining Projects

The R language is a powerful open source functional programming language. At its core, R is a statistical programming language that provides impressive tools for data mining and analysis. It enables you to create high-level graphics and offers an interface to other languages. This means R is best suited to producing data and visual analytics through customization scripts and commands, instead of the typical statistical tools that provide tick boxes and drop-down menus for users.

This video course explores data mining techniques, showing you how to apply different mining concepts to various statistical and data applications in a wide range of fields. We will teach you about R and its application to data mining, and give you relevant and useful information you can use to develop and improve your applications. It will help you complete complex data mining cases and guide you through handling issues you might encounter during projects.

Course Objectives
  • Make use of statistics and programming to understand data mining concepts and their application
  • Use R programming to apply statistical models to data
  • Use various libraries available in R CRAN (comprehensive R archives network) in data mining
  • Apply data management steps to handle large datasets
  • Get to know various data visualization libraries available in R to represent data
Curriculum
Module 1:

Data Manipulation Using In-Built R Data

Module 2:

Exploratory Data Analysis With Automobile Data

Module 3:

Visualizing Diamond Dataset

Module 4:

Regression With Automobile Data

Module 5:

Market Basket Analysis With Groceries Data

Instructor

Pradeepta Mishra is a data scientist, predictive modeling expert, deep learning and machine learning practitioner, and econometrician. He currently leads the data science and machine learning practice for Ma Foi Analytics, Bangalore, India. Ma Foi Analytics is an advanced analytics provider for Tomorrow's Cognitive Insights Ecology, using a combination of cutting-edge artificial intelligence, a proprietary big data platform, and data science expertise. He holds a patent for enhancing the planogram design for the retail industry. Pradeepta has published and presented research papers at IIM Ahmedabad, India. He is a visiting faculty member at various leading B-schools and regularly gives talks on data science and machine learning.

Pradeepta has spent more than 10 years solving various projects relating to classification, regression, pattern recognition, time series forecasting, and unstructured data analysis using text mining procedures, spanning across domains such as healthcare, insurance, retail and e-commerce, manufacturing, and so on.

If you have any questions, don't hesitate to look him up on Twitter via @mishra1_PK—he will be more than glad to help a fellow web professional wherever, whenever.

Certification

A test will be conducted at the end of the course. On completion of the test with a minimum of 70% marks, training.com will issue a certificate of successful completion from NIIT.

Five re-attempts will be provided in case the candidate scores less than 70%.

A Participation certificate will be issued if the candidate does not score 70% after five attempts.

Pre-requisites

Basic knowledge of data analysitcs and basic programming background with Math or Statistics background.

FAQs

Who should go for this Course?

This course comes as an ideal choice for Data Science professionals involved in complex data analytics and data mining techniques. Professionals working on Data Mining Projects can also pursue this course to help them gain an extra edge over sophisticated data mining algorithms development using R Language.

Course Features

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