research

Intended for: research teams, data science projects, ML engineering. Extends: managed

Managed plus data, ML, AI, and research-documentation skills.

Highlights

Data: data-science, data-pipeline, data-quality, data-visualization, feature-engineering, pandas-polars, database-modeling, sql-patterns
AI/ML: ai-fundamentals, ml-pipeline, prompt-engineering, llm-evaluation, embedding-vectordb, rag-engineering, code-generation
Research authoring: latex-authoring, documentation, infographics, excalidraw
Infrastructure bits research projects touch: shell-scripting, container-orchestration