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Courses>Data Science>Elements of Data Science and Statistical Learning with R
Elements of Data Science and Statistical Learning with R
Price:Paid
Length:4 months
Content type:video
level:beginner
Language:English
Category:Computer Science
SubCategory:Data Science
Updated:25 February 2024
Published:18 December 2022
Similar courses
Opportunities
.
Courses>Data Science>Elements of Data Science and Statistical Learning with R
Elements of Data Science and Statistical Learning with R
Tags
r programming
computer science
data science
statistical modeling
PreviewOne of the broad goals of data science is examining raw data with the purpose of identifying their structure and trends, and deriving conclusions and hypotheses from the latter.
Description

One of the broad goals of data science is examining raw data with the purpose of identifying their structure and trends, and deriving conclusions and hypotheses from the latter. In the modern world awash with data, data analytics is more important than ever to fields ranging from biomedical research, space and weather science, finance, business operations, and production, through marketing and social media applications. This course provides an intensive introduction to various statistical learning methods; the R programming language, a very popular and powerful platform for scientific and statistical analysis and visualization, is also introduced and used throughout the course. We discuss the fundamentals of statistical testing and learning, and cover topics of linear and non-linear regression, regularization, unsupervised methods (principle component analysis [PCA] and clustering), and supervised classification, including support vector machines, random forests, neural nets, using datasets drawn from diverse domains. This course is geared less toward theory (although some are presented, mostly qualitatively), and more toward developing intuition and the right way of thinking about statistical problems, as well as building practical skills through multiple, incremental assignments and extensive experimentation.

Course Content
Elements of Data Science and Statistical Learning with R
Price:Paid
Length:4 months
Content type:video
level:beginner
Language:English
Category:Computer Science
SubCategory:Data Science
Updated:25 February 2024
Published:18 December 2022
Similar courses
Opportunities
.
Author
Andrey SivachenkoWeb Site
Similar courses
Opportunities
Make the most out of your online education
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Careertail
Courses>Data Science>Elements of Data Science and Statistical Learning with R
Elements of Data Science and Statistical Learning with R
Price:Paid
Length:4 months
Content type:video
level:beginner
Language:English
Category:Computer Science
SubCategory:Data Science
Updated:25 February 2024
Published:18 December 2022
Similar courses
Opportunities
.
Courses>Data Science>Elements of Data Science and Statistical Learning with R
Elements of Data Science and Statistical Learning with R
Tags
r programming
computer science
data science
statistical modeling
PreviewOne of the broad goals of data science is examining raw data with the purpose of identifying their structure and trends, and deriving conclusions and hypotheses from the latter.
Description

One of the broad goals of data science is examining raw data with the purpose of identifying their structure and trends, and deriving conclusions and hypotheses from the latter. In the modern world awash with data, data analytics is more important than ever to fields ranging from biomedical research, space and weather science, finance, business operations, and production, through marketing and social media applications. This course provides an intensive introduction to various statistical learning methods; the R programming language, a very popular and powerful platform for scientific and statistical analysis and visualization, is also introduced and used throughout the course. We discuss the fundamentals of statistical testing and learning, and cover topics of linear and non-linear regression, regularization, unsupervised methods (principle component analysis [PCA] and clustering), and supervised classification, including support vector machines, random forests, neural nets, using datasets drawn from diverse domains. This course is geared less toward theory (although some are presented, mostly qualitatively), and more toward developing intuition and the right way of thinking about statistical problems, as well as building practical skills through multiple, incremental assignments and extensive experimentation.

Course Content
Elements of Data Science and Statistical Learning with R
Price:Paid
Length:4 months
Content type:video
level:beginner
Language:English
Category:Computer Science
SubCategory:Data Science
Updated:25 February 2024
Published:18 December 2022
Similar courses
Opportunities
.
Author
Andrey SivachenkoWeb Site
Similar courses
Opportunities
Make the most out of your online education
Careertail
Copyright © 2021 Careertail.
All rights reserved
Quick Links
Get StartedLog InAbout UsCourses
Company
BlogContactsPrivacy PolicyCookie PolicyTerms and Conditions
Stay up to date
Trustpilot