Contact me to organize workshops on algorithm engineering, or for consultations on how to improve your R&D workflows.
Common pain points I can address
- Pragmatic advice to help make sense of MLOps/DevOpsInfra/Cloud solutions, decide what to buy/fork/build…
- Build a roadmap to improve engineers' workflows, collaboration and infrastructure across departments.
- Implement solutions to help your algorithm engineers and data scientists waste less time toiling with the “logistics” of preparing, organizing, comparing and sharing their experiments.
- Evangilize the software engineering culture in organizations: reproduciblity, everything-as-code, data-driven…
- Create a Vision for infra/platform teams
Contact me for more information.
- Help data scientists and algorithm engineers be more productive
- Refreshers on algorithm development best practices
- Tooling and automation
- How to communicate results
- Cultivating a product-first vision
- Spread the software engineering culture to algorithm engineers
- Encourage everything-as-code, reproducibility, data-driven approaches
- Transitioning from writing scripts to building systems
- Help everybody understand code sharing and reuse
- Focused in-depth sessions
- Workflows and CI for algorithm engineering.
- “Building web applications” for algorithm engineers: from python’s streamlit to API and JS. When to make the switch?
- Software engineering for collaboration and reproducible science.
- Tour of the Python scientific computing ecosystem.
- Getting good-enough at visualization.
- Gluing open-source projects together.
- Quick wins for C++ projects
Get in touch to customize a course for you.