Resources
Resources for self-guided learning on programming, data science, and other skills related to computational research.
- Columbia Office of Research
- Open Scholarship Services, Columbia University Libraries
- Research Computing Services, CU Information Technology
- High Performance Computing, CU Information Technology
- Research Data Services, Columbia University Libraries
- Shared Research Computing Policy Advisory Committee
- Data Science Institute
- National Student Data Corps Video Library: Videos on data science topics based on IBM’s OpenDS4All curriculum, as well as student-created SQL and R educational materials, data science use cases, and more, presented by data enthusiasts from around the world
- CodeRefinery: Lessons and workshops for academics that need instruction on software, computing, and data with focus on reusability, reproducibility, and openness
- The Missing Semester of Your CS Education: MIT-developed class that covers all the topics they consider crucial to be an effective computer scientist and programmer
- INTERSECT Research Software Engineering Training: Software development and engineering training to intermediate and advanced developers of research software; compiles self-guided learning materials and offers an annual week-long summer bootcamp
- Cornell Virtual Workshops: Learning platform with trainings on programming languages (e.g. Python, R, MATLAB), parallel computing, code optimization, and data analysis. The platform supports learning communities around the world, with code examples from national systems such as Frontera, Stampede2, and Jetstream2.
- Data Science Resource Repository (DSSR): Curated set of 1,300+ resources for learners, educators, researchers, career explorers, and professionals that promotes data science literacy.
- Python Tutorials for Digital Humanities: Short, digestible YouTube videos (under 15-minutes) focused on teaching Python applications that are useful to non-STEM academics, such as NLP techniques (text analysis, named entity recognition, SpaCy), and leveraging JSON files.
LinkedIn Learning
Columbia University provides LinkedIn Learning access to faculty, staff, and students. LinkedIn Learning is an online service that provides video-based tutorials and resources on various web and software technology you might wish to explore. Below you will find login information to LinkedIn Learning courses that may be helpful in learning computational research skills. Please note that these resources have not yet been evaluated, but we welcome feedback on specific LinkedIn Learning courses or suggestions for alternatives. Please email those to [email protected].
Programming Foundations
Python
- Getting Started with Python (learning path)
- Advance Your Skills in Python (learning path)
- Pandas Essential Training
R
- Getting Started with R for Data Science (learning path)
- R for Data Science: Lunch Break Lessons
- Learning the R Tidyverse
SQL
- From Excel to SQL
- SQL Essential Training
- Learning SQL Programming
- Level Up: SQL (code challenges)
- Level Up: Advanced SQL (code challenge)
- Using SQL with Python
Working with Data
- Python for Data Analysis: Solve Real-World Challenges
- Data Visualization (learning path)
- Master the Concepts of Data Visualization and Storytelling (learning path)
Git & version control
APIs
Project management