R Programming Skill Assessment

R Programming Quiz

mtcars %>%
  group_by(cyl) %>%
  summarise(mean_mpg = mean(mpg))
  

Scoring Guide & Course Recommendations

0-30: Beginner Level

• Skill Level: New to R programming

• Recommended Coursera Courses:

  1. R Programming by Johns Hopkins University

     • R basics

     • Data types and structures

     • Basic functions

  2. Introduction to R for Data Science by IBM

     • Programming fundamentals

     • Basic data manipulation

  3. Data Science: Foundations using R by Johns Hopkins

     • R basics

     • Data manipulation

     • Basic visualization

40-70: Intermediate Level

• Skill Level: Familiar with R basics, ready for advanced concepts

• Recommended Coursera Courses:

  1. Advanced R Programming by Johns Hopkins University

     • Data manipulation with dplyr

     • Advanced visualization

     • Statistical analysis

  2. Data Analysis with R by IBM

     • Statistical methods

     • Data analysis

     • Hypothesis testing

  3. Data Visualization & Dashboarding with R Specialization by Johns Hopkins

     • ggplot2 mastery

     • Complex visualizations

     • Interactive graphics

80-100: Advanced Level

• Skill Level: Experienced R programmer

• Recommended Coursera Courses:

  1. Clustering and Classification with Machine Learning in R by Packt

     • Machine learning techniques in R

     • Data pre-processing and feature selection

  2. Advanced R Programming by Johns Hopkins

     • Advanced r programming techniques

     • Professional package development

  3. Machine Learning Algorithms with R in Business Analytics by University of Illinois

     • Regression analysis for business problems

     • Comprehensive machine learning framework

Skills Covered by Level

Beginner Level

• Basic syntax

• Data types and structures

• Basic functions

• Simple data manipulation

• Basic plotting

• Reading/writing data

Intermediate Level

• Data wrangling with tidyverse

• Statistical analysis

• Advanced visualization

• Package usage

• Basic modeling

• Data cleaning

Advanced Level

• Machine learning

• Advanced statistics

• Package development

• Production deployment

• Performance optimization

• Complex data analysis

Career Paths

• Beginner Level: Junior Data Analyst, Research Assistant, Statistical Assistant

• Intermediate Level: Data Analyst, Biostatistician, Market Research Analyst

• Advanced Level: Data Scientist, Senior Statistician, Quantitative Researcher