I started with simple seed code and, through the AI Augmented Exploratory Learning (AAEL) framework, built what I call a killer pipeline. By working alongside a large language model (LLM), each step became a learning cycle of exploration, iteration, and refinement.
This pipeline now:
Reads and normalizes MLS sales data
Dedupes records for accuracy
Integrates Freddie Mac rate data
Computes monthly and YTD KPIs across cities and ZIP codes
Exports a complete Excel bundle for audit and presentation
Auto generates 11 charts that are publication ready
This is not just a script. It is a system that blends data engineering, analytics, visualization, and automation into a repeatable and auditable workflow. The advanced part is not only the outputs, but also how it was built. AAEL shows that when humans and AI co create, the process itself becomes an education.
For me this pipeline is proof that LLMs, guided by AAEL, can accelerate both innovation and learning.
Robert Foreman
Doctoral Student in Educational Technology
Central Michigan University
📧 forem1r@cmich.edu
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