Resources
Below you will find resources and other information on programming, data science, and other skills related to computational research.
- Computational Research Training Opportunities
- Data Science Institute
- Digital Scholarship Group, Columbia University Libraries
- Research Computing Services, CU Information Technology
- Research Data Services, Columbia University Libraries
- Shared Research Computing Policy Advisory Committee
Python
- Getting Started with Python
- Getting Started with Python
- Pandas: the bare basics
- Intro to SpaCy
- PyMC3 for Probabilistic Programming
- Diving into TensorFlow 2.0
Web Development
Haskell
Data Cleaning
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].
Programing 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
- Applied Analytics Club
- Columbia Data Science Society is an organization of students from throughout the University interested in data science and its applications