Enabling Research

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High-quality research depends on strong infrastructure from the earliest stages of the process. Before fieldwork begins, research teams need members with the right set of skills, clearly defined protocols, and access to the appropriate tools and resources. Impact Analytics supports this early stage of the research lifecycle by helping teams identify operational constraints, design technical solutions, and build the systems that enable rigorous and reproducible research.

 

CONTINUING EDUCATION SERIES

Public access to materials and session recordings of previous continuing education series.

A conceptual and practical introduction to AI coding agents: what they are, how they work, and how to get started using them in a research coding environment.

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AI Onboarding Part 1: Memory Files - Why and how to create these “AI Readme”

Introduction to memory files (ReadMe/CLAUDE.md), their role in personalizing AI coding assistants, and how to build and maintain them.

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AI Onboarding Part 2: Skills - Improving AI workflows specific to your text

Hands-on introduction to AI skills as reusable workflow tools. Covers how to use existing AI skills and best practices for developing custom skills. It will include demonstrations from staff who have built their own skills. We expect to repeat this session regularly to feature new skills.  

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This training focuses on how to use Git in the context of research and data science. It assumes no prior experience with Git but is also relevant for users with some familiarity. By the end of the session, you'll be ready to start contributing to a project already hosted on GitHub.

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An intuitive introduction to AI agents, with a focus on coding agents and how they actually work and can be used on World Bank computers. Covering difference between LLMs and agents, explain the agentic loop in plain terms, and show how context, tools, memory, and skills influence the quality of results.

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