IA para Analistas de Datos

Resumen

Use AI across every stage of your data analysis. Write sharper prompts, audit data quality, find insights worth chasing, and ship work you can trust.

Your Practical Guide to AI-Augmented Data Analysis AI is changing how data analysts work, and this course shows you how to use it well. You'll learn to embed an AI assistant into every stage of your analysis workflow, from interrogating raw data to delivering insights leadership will act on.

DataCamp provides a built-in AI Data Assistant so you can practice on real datasets from the very first lesson. No technical background or external AI subscription required.

Write Prompts That Get Defensible Analysis Vague prompts produce vague output. This course teaches the GCSE framework (Goal, Context, Scope, Example) for turning open-ended business questions into precise instructions an AI can act on.

You'll practice on realistic scenarios across a coffee chain, a SaaS support desk, and a retail buyer's office, and learn how to spot the AI risks that hide inside polished-looking responses:

probabilistic variation, hallucination, sycophancy, and missing context. Audit Data Quality, Enrich Fields, and Find Insights Worth Chasing Most AI demos skip the messy middle.

This course doesn't. You'll work through the analyst loop on real datasets:

interrogate data for fuzzy duplicates, impossible timestamps, and missing values; enrich raw fields by using AI as both doer (executing the work) and advisor (deciding what's worth doing in the first place); then surface insights across trends, distributions, differences, and outliers.

Every finding gets pressure-tested before it reaches a stakeholder. Tell Stories That Land, Then Verify Before They Ship A dashboard or one-paragraph story is only as good as the verification behind it.

You'll learn to compress dashboard discovery and prototyping from weeks to an afternoon, tailor data stories to the audience and the decision in front of you, and apply the S.P.O.T. framework (Sample-and-trace, Peer-review, Order-of-magnitude check, Test-boundaries) to catch polished-but-wrong output before it reaches leadership. The capstone runs a complete AI-first analysis on a US retail chain, then closes with a bonus lesson from the Snowflake team on Snowflake Cortex.

By the time you complete this course, you'll have a repeatable framework for using AI across every stage of analysis, from prompt to dashboard to written recommendation, and the judgment to know when to trust the result, when to verify, and when to push back.

Programa

• Aumentando el Análisis de Datos con IA
Configura tu conjunto de herramientas de analista aumentado con IA. Aprende dónde encaja la IA a lo largo del ciclo de análisis de cinco etapas, domina el marco de indicaciones GCSE para convertir solicitudes vagas en recomendaciones accionables, y elige la forma correcta de conectar la IA a tus datos: archivos planos, MCP o una capa semántica gobernada.
• Explorando Datos y Desarrollando Perspectivas
Pasa de datos brutos a perspectivas que puedas defender. Interroga la calidad de los datos para detectar duplicados borrosos, valores faltantes y marcas de tiempo imposibles; enriquece campos brutos con IA tanto como ejecutor y asesor; luego encuentra perspectivas que valga la pena perseguir a través de tendencias, distribuciones, diferencias y valores atípicos, y verifica cada una antes de que llegue a un interesado.
• Narrativa Visual y Actuar sobre Perspectivas
Convierte hallazgos en paneles y narrativas que impacten. Comprime el descubrimiento y prototipado de paneles de semanas a una tarde, adapta historias de datos para la audiencia y decisión frente a ti, y protege contra salidas aparentemente pulidas pero incorrectas con el marco de verificación S.P.O.T.
• Proyecto de Culminación: Un Análisis Completo con IA
Realiza un análisis completo con IA en Board and Beyond, una cadena minorista de EE. UU. Audita la calidad de los datos, identifica los enriquecimientos que un gerente de categorías realmente usaría, revela y verifica un hallazgo principal, construye un panel que respalde una decisión de expansión y entrega una historia de un párrafo a la dirección.

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Impartido por

Andy Cotgreave

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Materias

Data Science