al Gael Alberto Lara Peña | Portfolio

Data Engineering Student • UPY

Building reliable data pipelines and practical ML systems.

I focus on end-to-end projects: ingestion, transformation, orchestration, storage, visualization, and deployment. I like clean documentation, reproducible setups, and measurable performance.

Location
México
Focus
Data pipelines • ML • Cloud • SQL • APIs

About

This portfolio highlights selected work across data engineering, cloud deployment, and applied machine learning. The goal is clarity: what was built, why, and how to reproduce it.

What I work on

ETL/ELT workflows, orchestration (Airflow/Kafka), storage layers (SQL/NoSQL), dashboards, and performance profiling for compute-heavy routines.

How I work

I prefer simple architectures, readable code, clean commits, and structured documentation. I aim for deployments that run consistently across machines.

Certifications

Verified learning milestones and training completed.

Google

Data Analytics Certificate

Data Analysis fundamentals and deployment.

University of Michigan

Python for Everybody Specialization

Coursework focused on practical data workflows and python.

NVIDIA

Computer Vision for Industrial Inspection

GPU and applied ML training, augmenting and deployment for the industry.

Projects

Selected projects with emphasis on scope, outcome, and implementation.

Neurocat - Neural Network

Designed and delivered in team collaboration, a neural network focused on cat images.

  • Prototype Neural Network trained to identify cat images.

NASA Hackathon 2025 - Exoplanets AI Verifier

Hackathon

Prototype system for assisting with exoplanet signal verification using machine learning, interactive visualization, and a simple web interface.

  • ML pipeline experimentation (feature engineering + evaluation).
  • Web UI to explore predictions and data context.

Events

Academic and community activities that complement project work.

UPY Open house • 2024 • Coordinator

Workshop Coordinator (@ UPY)

Hands-on academic workshop and collaborative learning regarding Neural Networks.

Hackathon • 2025 • Participation

NASA Space Apps / Hackathon Event (@ Anahuac)

Rapid prototyping, teamwork, and applied problem solving.

Contact

For collaboration, opportunities, or project discussion.