We talked about:

Johanna’s background Open science course and reproducible papers Research software engineering Convincing a professor to work on software instead of papers The importance of reproducible analysis Why academia is behind on software engineering The problems with open science publishing in academia The importance of standard coding practices How Johanna got into research software engineering Effective ways of learning software engineering skills Providing data and analysis for your project Johanna’s initial experience with software engineering in a project Working with sensitive data and the nuances of publishing it How often Johanna does hackathons, open source, and freelancing Social media as a source of repos and Johanna’s favorite communities Contributing to Git repos Publishing in the open in academia vs industry Johanna’s book and resource recommendations Conclusion

Links:

The Society of Research Software Engineering,  plus regional chapters: https://society-rse.org/ The RSE Association of Australia and New Zealand: https://rse-aunz.github.io/ Research Software Engineers (RSEs) The people behind research software: https://de-rse.org/en/index.html The software sustainability institute: https://www.software.ac.uk/ The Carpentries (beginner git and programming courses): https://carpentries.org/ The Turing Way Book of  Reproducible Research: https://the-turing-way.netlify.app/welcome

Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp

Join DataTalks.Club: https://datatalks.club/slack.html

Our events: https://datatalks.club/events.html

We talked about:

Tomasz’s background What Tomasz did before DataOps (Data Science) Why Tomasz made the transition from Data science to DataOps What is DataOps? How is DataOps related to infrastructure? How Tomasz learned the skills necessary to become DataOps Becoming comfortable with terminal The overlap between DataOps and Data Engineering Suitable/useful skills for DataOps Minimal operational skills for DataOps Similarities between DataOps and Data Science Managers Tomasz’s interesting projects Confidence in results and avoiding going too deep with edge cases Conclusion

Links:

Terminal setup video, 19 minutes long: https://www.youtube.com/watch?v=D2PSsnqgBiw Command line videos, one and a half hour to become somewhat comfy with the terminal: https://www.youtube.com/playlist?list=PLIhvC56v63IKioClkSNDjW7iz-6TFvLwS Course from MIT talking about just that (command line, git, storing secrets): https://missing.csail.mit.edu/

ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp

Join DataTalks.Club: https://datatalks.club/slack.html

Our events: https://datatalks.club/events.html