• 09899714317

Benefits of the course

  • R programming fundamentals: Learn the basics of the R programming language, such as variables, data types, functions, and loops.
  • Data manipulation: Learn how to use R to import, clean, and manipulate data from a variety of sources, such as CSV files, SQL databases, and APIs.
  • Exploratory data analysis (EDA): Learn how to use R to perform EDA, which is the process of exploring and understanding data. This includes tasks such as calculating descriptive statistics, creating data visualizations, and identifying patterns and trends.
  • Statistical analysis: Learn how to use R to perform statistical analysis on data. This includes tasks such as hypothesis testing, regression analysis, and classification.
  • Data visualization: Learn how to use R to create informative and engaging data visualizations. This includes using libraries such as ggplot2 to generate charts, graphs, and maps.

Topics for this course

15 Lessons 142 hours

Module 1: Introduction

What is Data Science
Application of Statistics and Programming in Data Science
Importance of Data in Al, Data Science and Data Analytics

Module 2 : Statistics

Module 3 : R Programming

Module 4 : DA with R


  • No prior coding knowledge is required or assumed

Target Audience

  • Career changers: People who are interested in transitioning to a career in data science or data analytics.
  • Students: Undergraduate and graduate students in computer science, data science, statistics, and other related fields.
  • Professionals: People who work in a variety of fields and want to learn how to use data analytics to improve their work. This includes people who work in business intelligence, marketing, finance, healthcare, and more.

  • Duration 142 hours
  • Lessons15
  • Skill levelExpert
  • CategoryData Analytics

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