Learn valuable insights and best practices for conducting research and programming in computer science graduate school in this 53-minute lecture by Dave Churchill. Explore essential topics such as version control, file backup, portfolio building, reference management, experiment organization, and data visualization. Discover the differences between typical and ideal thesis workflows, understand the importance of experiment repeatability, and gain practical knowledge on using Docker containers. Benefit from Churchill's decade of experience as he shares lessons learned and provides general tips for success in computer science research and programming.
Computer Science Graduate School Research and Programming Best Practices
Overview
Syllabus
- Introduction
- Which advice to believe?
- Version Control / File Backup
- GitHub Repos / Portfolio Building
- Bibliography / Reference Managers
- Experiments / Methodology
- Experiment Organization
- Typical Thesis Workflow
- Ideal Thesis Workflow
- Experiment Repeatability
- Example Experiment Configuration
- Visualize Your Data
- Example Real-Time Visualization
- Documentation
- Docker Containers
Taught by
Dave Churchill
