Data Science Ph.D Program

Commonly used Blogs on R Programming and Python Programming

for Data Science

Online Resources for R Programmers in Data Science

• The Comprehensive R Archive Network (CRAN)
  https://cran.r-project.org/

• RStudio Documentation
  IDE Guides & Tutorials: https://docs.rstudio.com/

• Tidyverse
  Core Packages & Cheat Sheets: https://www.tidyverse.org/

• Swirl (Interactive R Lessons)
  https://swirlstats.com/

• DataCamp – R Tracks
  https://www.datacamp.com/tracks/data-scientist-with-r

• Codecademy – Learn R
  https://www.codecademy.com/learn/learn-r

• Coursera – Johns Hopkins Data Science Specialization
  https://www.coursera.org/specializations/jhu-data-science

• edX – Introduction to R for Data Science (Microsoft)
  https://www.edx.org/course/introduction-to-r-for-data-science

• Udemy – Advanced R Programming
  https://www.udemy.com/course/advanced-r-programming/

• “R for Data Science” (Grolemund & Wickham)
  https://r4ds.had.co.nz/

• “Advanced R” (Hadley Wickham)
  https://adv-r.hadley.nz/

• “Practical Statistics for Data Scientists”
  https://www.oreilly.com/library/view/practical-statistics-for/9781491952955/

• RStudio Community Forum
  https://community.rstudio.com/

• Stack Overflow (R Tag)
  https://stackoverflow.com/questions/tagged/r

• R-bloggers
  https://www.r-bloggers.com/

• Shiny by RStudio
  https://shiny.rstudio.com/

• Plotly for R
  https://plotly.com/r/

• TidyTuesday (Sample Datasets)
  https://github.com/rfordatascience/tidytuesday

• UCI Machine Learning Repository
  https://archive.ics.uci.edu/ml/index.php

Online Resources for Python Programmers in Data Science

• Python.org (Official Docs)
  https://www.python.org/doc/

• NumPy
  https://numpy.org/doc/

• pandas
  https://pandas.pydata.org/docs/

• Matplotlib
  https://matplotlib.org/stable/contents.html

• SciPy
  https://docs.scipy.org/doc/

• scikit‑learn
  https://scikit-learn.org/stable/documentation.html

• Kaggle Learn
  https://www.kaggle.com/learn

• DataCamp – Python Tracks
  https://www.datacamp.com/tracks/data-scientist-with-python

• Codecademy – Learn Python
  https://www.codecademy.com/learn/learn-python-3

• Coursera – IBM Data Science Professional Certificate
  https://www.coursera.org/professional-certificates/ibm-data-science

• edX – Introduction to Python for Data Science (Microsoft)
  https://www.edx.org/course/introduction-to-python-for-data-science

• Udacity – AI Programming with Python Nanodegree
  https://www.udacity.com/course/ai-programming-python-nanodegree--nd089

• “Python for Data Analysis” (Wes McKinney)
  https://www.oreilly.com/library/view/python-for-data/9781491957653/

• “Hands‑On Machine Learning with Scikit‑Learn, Keras, and TensorFlow”
  https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/

• “Deep Learning with Python” (François Chollet)
  https://www.manning.com/books/deep-learning-with-python

• Stack Overflow (Python Tag)
  https://stackoverflow.com/questions/tagged/python

• Reddit – r/learnpython
  https://www.reddit.com/r/learnpython/

• Reddit – r/datascience
  https://www.reddit.com/r/datascience/

• GitHub Trending (Data Science)
  https://github.com/trending/python?since=daily

• Google Colab
  https://colab.research.google.com/

• Binder (MyBinder.org)
  https://mybinder.org/

• TensorFlow Tutorials
  https://www.tensorflow.org/tutorials

• PyTorch Tutorials
  https://pytorch.org/tutorials/

• Fast.ai Courses
  https://course.fast.ai/

• Kaggle Datasets
  https://www.kaggle.com/datasets

• OpenML
  https://www.openml.org/