R DC Skill & Career Tracks

Completed R Career Tracks at DataCamp

R Programmer ( old version )

  1. Introduction to R
  2. Intermediate R
  3. Intermediate R: Practice
  4. Introduction to Importing Data in R
  5. Intermediate Importing Data in R
  6. Cleaning Data in R
  7. Importing & Cleaning Data in R: Case Studies
  8. String Manipulation with stringr in R
  9. Writing Functions in R
  10. Object-Oriented Programming with S3 and R6 in R

Data Scientist with R

  1. Introduction to R
  2. Intermediate R
  3. Introduction to the Tidyverse
  4. Introduction to Importing Data in R
  5. Intermediate Importing Data in R
  6. Cleaning Data in R
  7. Importing & Cleaning Data in R: Case Studies
  8. Writing Functions in R
  9. Data Manipulation in R with dplyr
  10. Joining Data in R with dplyr
  11. Introduction to SQL
  12. Data Visualization with ggplot2 (Part 1 & 2)
  13. Working with Dates and Times in R
  14. Introduction to Data in R
  15. Exploratory Data Analysis in R
  16. Exploratory Data Analysis in R: Case Study
  17. Correlation and Regression in R
  18. Cluster Analysis in R
  19. Supervised Learning in R: Classification
  20. Unsupervised Learning in R
  21. Joining Data in SQL
  22. Reporting with R Markdown

Data Analyst with R

  1. Introduction to R
  2. Intermediate R
  3. Introduction to the Tidyverse
  4. Introduction to Importing Data in R
  5. Intermediate Importing Data in R
  6. Cleaning Data in R
  7. Importing & Cleaning Data in R: Case Studies
  8. Data Manipulation in R with dplyr
  9. Joining Data in R with dplyr
  10. Data Visualization with ggplot2 (Part 1)
  11. Sentiment Analysis in R: The Tidy Way
  12. Introduction to Data in R
  13. Exploratory Data Analysis in R
  14. Exploratory Data Analysis in R: Case Study
  15. Correlation and Regression in R
  16. Reporting with R Markdown

Quantitative Analyst with R

  1. Introduction to R for Finance
  2. Intermediate R for Finance
  3. Manipulating Time Series Data with xts and zoo in R
  4. Importing and Managing Financial Data in R
  5. Time Series Analysis in R
  6. ARIMA Modeling with R
  7. Case Studies: Manipulating Time Series Data in R
  8. Forecasting in R
  9. Visualizing Time Series Data in R
  10. Introduction to Portfolio Analysis in R
  11. Intermediate Portfolio Analysis in R
  12. Bond Valuation and Analysis in R
  13. Credit Risk Modeling in R
  14. Quantitative Risk Management in R
  15. Financial Trading in R

 

Completed R Skill Tracks at DataCamp

R Programming

  1. Introduction to R
  2. Intermediate R
  3. Writing Efficient R Code
  4. Parallel Programming in R

Importing and Cleaning Data with R

  1. Introduction to Importing Data in R
  2. Intermediate Importing Data in R
  3. Cleaning Data in R
  4. Importing and Cleaning Data in R: Case Studies

Data Manipulation with R

  1. Working with Data in Tidyverse
  2. Exploratory Data Analysis in R: Case Study
  3. Data Manipulation with data.table in R
  4. Joining Data with data.table in R

Statistics Fundamentals with R

  1. Introduction to Data in R
  2. Exploratory Data Analysis in R
  3. Correlation and Regression in R
  4. Multiple and Logistic Regression in R

Data Visualization with R

  1. Data Visualization with ggplot2 (Part 1)
  2. Data Visualization with ggplot2 (Part 2)
  3. Visualization Best Practices in R
  4. Data Visualization in R
  5. Data Visualization with lattice in R

Time Series with R

  1. Manipulating Time Series Data with xts and zoo in R
  2. Time Series Analysis in R
  3. ARIMA Modeling with R
  4. Forecasting in R
  5. Visualizing Time Series Data in R
  6. Case Studies: Manipulating Time Series Data in R

Applied Finance with R

  1. Bond Valuation and Analysis in R
  2. Introduction to Portfolio Analysis in R
  3. Intermediate Portfolio Analysis in R
  4. Financial Trading in R

Finance Basics with R

  1. Introduction to R for Finance
  2. Intermediate R for Finance
  3. Manipulating Time Series Data with xts and zoo in R
  4. Importing and Managing Financial Data in R

Machine Learning Fundamentals in R

  1. Supervised Learning in R: Classification
  2. Supervised Learning in R: Regression
  3. Unsupervised Learning in R
  4. Machine Learning Toolbox

Text Mining with R

  1. Introduction to Text Analysis in R
  2. String Manipulation with stringr in R
  3. Text Mining: Bag of Words
  4. Sentiment Analysis in R

Tidyverse Fundamentals with R

  1. Introduction to the Tidyverse
  2. Working with Data in the Tidyverse
  3. Modeling with Data in the Tidyverse
  4. Communicating with Data in the Tidyverse
  5. Categorical Data in the Tidyverse

Unsupervised Machine Learning with R

  1. Unsupervised Learning in R
  2. Cluster Analysis in R
  3. Factor Analysis in R
  4. Advanced Dimensional Reduction in R

Marketing Analytics with R

  1. Machine Learning for Marketing Analytics in R
  2. Choice Modeling for Marketing in R
  3. Building Response Models in R
  4. Introduction to Text Analysis in R

Statistical Inference with R

  1. Foundations of Inference in R
  2. Inference for Categorical Data in R
  3. Inference for Numerical Data in R
  4. Inference for Linear Regression in R

Probability and Distributions with R

  1. Foundations of Probability in R
  2. Multivariate Probability Distributions in R
  3. Probability Puzzles in R
  4. Mixture Models in R