Udemy - 2021 R 4.0 Programming for Data Science || Beginners to Pro

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2021 R 4.0 Programming for Data Science - Beginners to Pro [TutsNode.com] - 2021 R Programming for Data Science 3. Fundamentals of DataFrames in R Programming
  • 18. Data Frame Merge and Join Inner Join.mp4 (142.7 MB)
  • 18. Data Frame Merge and Join Inner Join.srt (16.0 KB)
  • 17. Groupby on DataFrame in R.srt (11.2 KB)
  • 14. Working with DateTime in DataFrame.srt (11.0 KB)
  • 19. Left, Right, and Outer Merge (Join) of DataFrame in R.srt (10.5 KB)
  • 1. Create DataFrame in R.srt (9.5 KB)
  • 10. Bind Rows rbind() and bind_rows().srt (9.2 KB)
  • 13. Conditional DataFrame Selection with subset().srt (8.7 KB)
  • 2. Get the DataFrame Details.srt (7.9 KB)
  • 4. Access DataFrames Like Matrix.srt (7.5 KB)
  • 8. Loading a DataFrame from .XML File.srt (7.3 KB)
  • 6. Loading a DataFrame from .CSV File.srt (6.9 KB)
  • 7. Load DataFrame from Excel .xlsx File.srt (6.7 KB)
  • 12. Data Frame Selection and Indexing.srt (6.2 KB)
  • 9. Loading a DataFrame from .json File.srt (6.0 KB)
  • 5. Modify a DataFrame.srt (5.2 KB)
  • 3. Working with [, [[ and $ Operator.srt (5.0 KB)
  • 15. Export DataFrame in .CSV File.srt (4.4 KB)
  • 14. Working with DateTime in DataFrame.mp4 (94.5 MB)
  • 11. Bind Columns cbind() and bind_cols().srt (3.9 KB)
  • 16. Data Frame Sorting.srt (2.7 KB)
  • 17. Groupby on DataFrame in R.mp4 (85.0 MB)
  • 19. Left, Right, and Outer Merge (Join) of DataFrame in R.mp4 (83.5 MB)
  • 13. Conditional DataFrame Selection with subset().mp4 (70.3 MB)
  • 10. Bind Rows rbind() and bind_rows().mp4 (64.4 MB)
  • 8. Loading a DataFrame from .XML File.mp4 (61.0 MB)
  • 1. Create DataFrame in R.mp4 (51.7 MB)
  • 7. Load DataFrame from Excel .xlsx File.mp4 (50.6 MB)
  • 2. Get the DataFrame Details.mp4 (48.0 MB)
  • 6. Loading a DataFrame from .CSV File.mp4 (46.1 MB)
  • 9. Loading a DataFrame from .json File.mp4 (45.0 MB)
  • 4. Access DataFrames Like Matrix.mp4 (40.3 MB)
  • 12. Data Frame Selection and Indexing.mp4 (39.9 MB)
  • 15. Export DataFrame in .CSV File.mp4 (37.2 MB)
  • 5. Modify a DataFrame.mp4 (34.6 MB)
  • 3. Working with [, [[ and $ Operator.mp4 (26.6 MB)
  • 11. Bind Columns cbind() and bind_cols().mp4 (20.7 MB)
  • 16. Data Frame Sorting.mp4 (19.7 MB)
2. R Programming Fundamentals
  • 23. Arrays Naming and Accessing the Values.srt (12.6 KB)
  • 5. Logical Operators.srt (10.1 KB)
  • 2. Rules of Variable Names in R.srt (9.7 KB)
  • 15. Vector Manipulation.srt (9.2 KB)
  • 25. If If-Else and If-Else-If Statements.srt (8.5 KB)
  • 21. Arithmetic Operations on Matrix.srt (8.4 KB)
  • 13. Colon () Operator for Vector Generation.srt (8.2 KB)
  • 26. repeat() and while() Loops.srt (8.1 KB)
  • 6. Assignment Operators.srt (2.7 KB)
  • 20. Introduction to Matrix.srt (8.0 KB)
  • 8. Function in R.srt (7.7 KB)
  • 9. Data Types in R.srt (7.7 KB)
  • 24. Factors in R.srt (7.6 KB)
  • 18. List Manipulation and Merging.srt (7.0 KB)
  • 28. next Statement and break Statement.srt (6.1 KB)
  • 27. for() Loop.srt (6.1 KB)
  • 7. Miscellaneous Operators.srt (6.0 KB)
  • 22. Arrays Introductions.srt (5.7 KB)
  • 4. Relational Operators.srt (5.6 KB)
  • 1. Variable Assignments.srt (5.3 KB)
  • 11. paste() Function for String Manipulation.srt (5.2 KB)
  • 3. Arithmetic Operators.srt (5.1 KB)
  • 19. List to Vectors and Vectors to List.srt (5.1 KB)
  • 14. Using [] Operator and c() Function to Access Vector Elements.srt (4.7 KB)
  • 10. Strings Assignment.srt (5.0 KB)
  • 17. Named List.srt (4.4 KB)
  • 16. List Creation.srt (4.2 KB)
  • 12. format() Function for Numeric Data Formatting.srt (3.9 KB)
  • 23. Arrays Naming and Accessing the Values.mp4 (80.6 MB)
  • 5. Logical Operators.mp4 (60.9 MB)
  • 24. Factors in R.mp4 (56.3 MB)
  • 2. Rules of Variable Names in R.mp4 (56.0 MB)
  • 13. Colon () Operator for Vector Generation.mp4 (53.1 MB)
  • 15. Vector Manipulation.mp4 (52.6 MB)
  • 8. Function in R.mp4 (52.0 MB)
  • 9. Data Types in R.mp4 (51.2 MB)
  • 21. Arithmetic Operations on Matrix.mp4 (45.2 MB)
  • 20. Introduction to Matrix.mp4 (43.3 MB)
  • 7. Miscellaneous Operators.mp4 (41.8 MB)
  • 18. List Manipulation and Merging.mp4 (38.0 MB)
  • 25. If If-Else and If-Else-If Statements.mp4 (37.6 MB)
  • 10. Strings Assignment.mp4 (37.0 MB)
  • 1. Variable Assignments.mp4 (36.3 MB)
  • 11. paste() Function for String Manipulation.mp4 (34.2 MB)
  • 12. format() Function for Numeric Data Formatting.mp4 (33.7 MB)
  • 22. Arrays Introductions.mp4 (31.0 MB)
  • 26. repeat() and while() Loops.mp4 (30.3 MB)
  • 4. Relational Operators.mp4 (30.2 MB)
  • 3. Arithmetic Operators.mp4 (29.2 MB)
  • 14. Using [] Operator and c() Function to Access Vector Elements.mp4 (29.0 MB)
  • 19. List to Vectors and Vectors to List.mp4 (27.8 MB)
  • 28. next Statement and break Statement.mp4 (26.8 MB)
  • 27. for() Loop.mp4 (25.1 MB)
  • 16. List Creation.mp4 (23.8 MB)
  • 17. Named List.mp4 (22.3 MB)
  • 6. Assignment Operators.mp4 (16.5 MB)
1. Introduction
  • 2. Download Code Files Do Not Skip This.html (0.1 KB)
  • 3. R-Studio Introduction.srt (9.7 KB)
  • 1. Install R and R-Studio for Data Science.srt (4.5 KB)
  • 3. R-Studio Introduction.mp4 (61.1 MB)
  • 1. Install R and R-Studio for Data Science.mp4 (20.8 MB)
  • 2.1 Udemy.zip (6.1 MB)
4. Jupyter Notebook Introduction for R Programming
  • 9. R Coding Practice with Jupyter Notebook vs R-Studio.mp4 (92.2 MB)
  • 4. R 4.x Installation in Anaconda with Jupyter Notebook.mp4 (79.4 MB)
  • 7. Jupyter Notebook Shortcuts Part 3.mp4 (65.1 MB)
  • 6. Jupyter Notebook Shortcuts Part 2.mp4 (53.0 MB)
  • 1. Jupyter Notebook Introduction.mp4 (40.5 MB)
  • 8. Jupyter Notebook Shortcuts Part 4.mp4 (36.1 MB)
  • 2. Anaconda Installation fo

Description


Description

Are you ready to accept the R Programming Challenge?

Want to analyze and get insights from your datasets?

This Course is for You!!!

You will learn R programming in a very interactive way. I will be explaining to you each line of code. You do not need any prior experience in coding. Anyone can start learning. We will start with R Programming and R-Studio set up on the computer thereafter I will be teaching you fundamentals of R Programming.

In this course, you learn:

How to install R-Packages
How to work with R-data types
What is R DataFrame, Matrices, Vectors etc.
How to work with DataFrames
How to perform join and merge operations on DataFrames
How to plot data using ggplot2 in R 4.0
Analysis of real-life dataset Covid-19

This course is in development. 20+ hours of lectures will be added to the course. Kindly, keep checking regularly.

—————————

THIS COURSE IS NOT COMPLETE YET. MACHINE LEARNING LECTURES WILL BE UPLOADED IN COUPLE OF WEEKS.

—————————
Who this course is for:

Data Scientist Beginners
R Programmers
Data Scientist who codes in R
Data Analyst who codes in R
Data Scientist managers, executives or students

Requirements

Anyone interested to become a Data Scientist or Data Analyst
No prerequisites require

Last Updated 12/2020



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Udemy - 2021 R 4.0 Programming for Data Science || Beginners to Pro

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3.5 GB
seeders:18
leechers:13
Udemy - 2021 R 4.0 Programming for Data Science || Beginners to Pro

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