Links

Important links will be here

• Course web page http://casimpkinsjr.radiantdolphinpress.com/pages/cogs108_ss1_23/index.html
• Course GitHub: https://github.com/drsimpkins-teaching/COGS108
• Course Canvas: https://canvas.ucsd.edu/courses/47460
• Assignment Submission: https://datahub.ucsd.edu

Team management

• https://www.nationalacademies.org/our-work/the-science-of-team-science
• https://research.upenn.edu/resources/hub/team/managing/
  
• https://doresearch.stanford.edu/resources-collaboration-and-team-science
  
• https://www.socra.org/blog/cultivating-an-effective-research-team-through-application-of-team-science-principles/
  
• https://www.ncbi.nlm.nih.gov/books/NBK310381/
  
• https://en.wikipedia.org/wiki/Science_of_team_science
  
• https://hbr.org/2018/10/managing-a-data-science-team

Resources

Helpful Resources for COGS 108 Students

Basic Python:

• Python Crash Course (book)
• Learn Python the Hard Way
• COGS 18 Materials notes; textbook

Online Python Courses/Practice:

• Codeacademy
• CodingBat
• LeetCode
• PythonPractice

Command Line or Terminal:

• Command Line for Beginners
• Linux Command Line
• Terminal Cheat Sheet
• Git Command Line Cheat Sheet

Version Control (git and GitHub):

• Getting Started with git
• GitHub Guide
• GitHub Desktop App Tutorial
• Git Command Line Resource
• Using git from the command line
  • Installing and using git (Part 1), by TA Ganesh (youtube, 22min tutorial)
  • merge conflicts and branching (Part 2), by IA Shubham Kulkarni (youtube, 8min tutorial)
• Using git with GitHub Desktop, by TA Sidharth Suresh (youtube, 13min tutorial)
• GIT & GITHUB TUTORIAL, from edureka!
  • with notes from TA Holly(Yueying Dong)
  • Personal Access Token Tutorial by IA-ish(?) Scott Yang
• Uh oh! My Jupyter notebook has loads of big images/plots and it is now too big to fit inside Github's file size limit.
  • https://pypi.org/project/ipynbcompress/


SQL Resources:

• PostgreSQL Exercises
• Mode Analytics

Data Visualization

• Data to Viz - help determining what visualization is appropriate; with code examples

More Data Science in Python Resources:

• Kaggle's learn pandas - for learning pandas (interactive programming)
• Python Data Science Handbook (book)
• Essential Cheat Sheets for Machine Learning and Deep Learning Engineers
• Python for Data Analysis(book)
• Learning Pandas

NLP (Natural Language Processing)

• NLP in Python (youtube video)