Practical GenAI in Data Analytics

Categories: AI4X
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About Course

Four live sessions, 20 hours, on your own data. You leave with a production-grade Analytics AI Operating System — Auto-EDA, text-to-SQL, forecasting, and bilingual narratives — you can run on Monday.

What you’ll be able to do

  • Profile and score data quality at scale with Auto-EDA
  • Query structured data in plain language with text-to-SQL
  • Run cohort and A/B analyses with statistical rigor
  • Build a conversational analytics layer over your own data
  • Generate forecasts and flag anomalies automatically
  • Ground bilingual (EN/AR) insights with retrieval (RAG)
  • Turn analysis into narratives tuned to three audiences
  • Defend a production-grade Analytics AI Operating System

Format: 4 weeks · ~5 hrs live + 6–8 self · Live online · Fridays Cairo · Mentor + take-home rubric.

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Course Content

Start here · Welcome & orientation
How your Data Analytics cohort works — schedule, support, and what you'll ship.

Week 1 · AI-Augmented Analyst Foundations
Stand up your analyst co-pilot and a read-only data layer, then profile any dataset with Auto-EDA and a data-quality scorecard.

Week 2 · Query & Analytical Layer
Query in plain language with text-to-SQL, then run EDA, statistics, and cohort + A/B analysis with rigor.

Week 3 · Presentation & Forward-Looking Layer
Build a conversational analytics layer and a forecasting + anomaly-detection engine leaders can act on.

Week 4 · Unstructured Data & Narrative Capstone
Add bilingual RAG over documents and an audience-tuned narrative generator, then defend your Operating System.

Capstone · Analytics AI Operating System
Build a production-grade Analytics AI Operating System on your own data, component by component, then defend it live.

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