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Data Science With R

Data Science With R

The course then introduces Machine Learning with techniques such as regression, classification, clustering, and density estimation, in order to solve various data problems.

Overview

Description
This course introduces R programming environment as a way to have hands-on experience with Data Science. It starts with a few basic examples in R before moving onto doing statistical processing. The course then introduces Machine Learning with techniques such as regression, classification, clustering, and density estimation, in order to solve various data problems.

Course Information

This course is for beginners, but it helps to have some basic understanding of statistics (mean, median, scatter plot) and preliminary knowledge of any programming. The course also assumes that you know how to download and install various programs/apps, and you are able to edit and debug simple programs

Writing simple R programs to do basic mathematical and logical operations
Loading structured data in a R environment for processing
Creating descriptive statistics and visualizations
Finding correlations among numerical variables
Using regression analysis to predict the value of a continuous variable
Building classification models to organize data into pre-determined classes
Organizing given data into meaningful clusters
Applying basic machine learning techniques for solving various data problems

Anyone interested in data sciences
Anyone who plans a career in data scientist,
Software developer whom want to learn data science,

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Course Specifications

Our great AI and Machine Learning courses include Artificial Intelligence, Coding and Programming. 

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Adult education is the non-credential activity of gaining skills and improved education. 

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Online education is electronically supported learning that relies on the Internet for teacher/student interaction. 

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A short course is a learning programme that gives you combined content or specific skills training in a short period of time. Short courses often lean towards the more practical side of things and have less theory than a university course – this gives you a more hands-on experience within your field of interest.

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Course duration is 24 hours.

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