Lesson Material
Lesson Material
Visit our Youtube channel to view recordings of previous sessions.
Installation instructions for Python and R can be found on GitHub repository.
By Topic
Python
- Biopython 10-minute demo
- CPU Multiprocessing in Python
- Cartography and Mapping in Python
- Continuous integration in Git with examples in Python
- Creating Packages in Python
- Debugging in Python
- Designing data analysis workflows
- Image Processing in Python
- Intermediate Topics in Python
- Intro to NLP
- Intro to Pandas DataFrames
- Intro to Python
- Introduction to Classes in Python
- Introduction to data analysis in Python
- Large Datasets in Python
- Machine Learning with scikit-learn
- Pandas for data analysis
- Plotting in Python
- Unit Testing in Python
R
- Data wrangling with dplyr and magrittr
- High Performance Loops in R
- Interactive Plotting with Shiny Apps
- Intermediate topics in R: Strings and factors
- Introduction to Machine Learning in R
- Introduction to R
- Introduction to ggplot2
- Making interactive plots using Shiny in R
- Making packages in R using devtools
- RStudio Debugging
- Reproducible Science in RStudio
- Resampling techniques in R: bootstrapping and permutation testing
Git
- (Brief) Introduction to Git + GitHub
- An Intermediate Look at Git + GitHub
- Collaborating on GitHub
- Collaborating on GitHub
- Continuous integration in Git with examples in Python
- Continuous integration on GitHub
- Using branches in Git
Misc
- Careers Outside Academia
- Code Review Overview
- Full Text Search with SQLite and Python
- Information from the Air: Software Defined Radio
- Intro to Inkscape for graphic design
- Intro to LaTeX
- Intro to LaTeX
- Intro to Pandoc and Markdown
- Intro to web development with HTML/CSS/JS
- Introduction to Bash
- Introduction to Databases and SQLite
- Introduction to Quantum Computing
- Introduction to Ruby
- Opening up your data
- RESTful Web Services in Science
- Web design with Jekyll/GitHub Pages
By Level
Beginner
- (Brief) Introduction to Git + GitHub
- Code Review Overview
- Collaborating on GitHub
- High Performance Loops in R
- Intro to Inkscape for graphic design
- Intro to LaTeX
- Intro to LaTeX
- Intro to Pandas DataFrames
- Intro to Pandoc and Markdown
- Intro to Python
- Intro to web development with HTML/CSS/JS
- Introduction to Bash
- Introduction to Databases and SQLite
- Introduction to Quantum Computing
- Introduction to R
- Introduction to Ruby
- Introduction to data analysis in Python
- Opening up your data
- Pandas for data analysis
- Plotting in Python
- Reproducible Science in RStudio
- Web design with Jekyll/GitHub Pages
Intermediate
- CPU Multiprocessing in Python
- Cartography and Mapping in Python
- Collaborating on GitHub
- Continuous integration in Git with examples in Python
- Continuous integration on GitHub
- Data wrangling with dplyr and magrittr
- Debugging in Python
- Designing data analysis workflows
- Image Processing in Python
- Information from the Air: Software Defined Radio
- Intermediate Topics in Python
- Intermediate topics in R: Strings and factors
- Intro to NLP
- Introduction to Classes in Python
- Introduction to Machine Learning in R
- Introduction to ggplot2
- Large Datasets in Python
- Machine Learning with scikit-learn
- Making packages in R using devtools
- RESTful Web Services in Science
- RStudio Debugging
- Resampling techniques in R: bootstrapping and permutation testing
- Using branches in Git