Data Science Journal Club Course¶
Intended for students interested in learning more about data science and its applications to research, the course is 1 credit hour pass/fail and offered every session (Fall, Spring, Summer). The course is listed as
GBSC 720-VTR JC- Data Science Club and sometimes also as
IDNE 790-VTR JC- Data Science Club. Students are largely expected to lead their own journey, with instructors facilitating and offering advice. We expect a good-faith effort to learn and grow in the course and the course has most value when students step outside their comfort zones. There are three student-led demonstrations required to pass, where we expect students to demonstrate how they have learned and grown from their exploration of the material.
Some of the topics covered by past students include:
- Learning to use High Performance Computing (HPC) resources
- Learning software development good practices
- Learning git and github
- Learning data organization good practices
- Jupyter notebooks
- R Markdown notebooks
- Data visualization
- Data analytics
- Data processing pipelines
- Machine learning
- Deep learning
The only prerequisite for the course is feeling comfortable using a computer. We are flexible with topics and welcome students of all levels of data science experience.
If you have questions about the course please feel free to reach out to Support.
The syllabus is available as a public webpage at https://s3.lts.rc.uab.edu/uab-rc-dsjc/syllabus.html, hosted on LTS.