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Data Science with R – Handling Data Efficiently with R

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About Course

Data science is a fascinating field that enables you to transform unprocessed data into comprehension, insight, and knowledge. The aim of “R for Data Science” is to assist you in learning the most crucial R tools necessary for data science.

Data exploration, data visualisation, predictive analytics, and descriptive analytics techniques are all covered in the Data Science with R Programming certification training. In this course, you will acquire knowledge of R packages, data import and export procedures in R, data structures commonly used in R, fundamental statistical concepts, cluster analysis techniques, and forecasting methods.

What Will You Learn?

  • Applying analytical techniques to derive insights and make data-driven business decisions.
  • Utilising R programming language and its packages for data analysis and statistical modeling.
  • Understanding different data structures and using visualizations to explore and present data.
  • Applying functions in R and utilizing the DPLYR package for data manipulation.
  • Creating visual representations of data using graphics capabilities in R.
  • Conducting statistical tests to evaluate hypotheses and make inferences about data.
  • Implementing the Apriori algorithm for association rule mining in large datasets.
  • Applying K-means and DBSCAN clustering algorithms to group similar data points together.

Course Content

Introduction

  • Course Introduction.
    00:00

Overview of Business Analytics

Data Structures

Data Visualisation

Regression Analysis

Clustering

Association

Course Completion Quiz

Student Ratings & Reviews

5.0
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3 years ago
This course was a true gem! The instructor's expertise and ability to break down complex concepts into understandable chunks were remarkable.
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