BackToBasics

Intent

This is a deliberate learning project, not an entrepreneurial one. The goal is to bridge the gap between my AI/ML/CV knowledge and the software engineering skills expected by CTOs and technical interviewers — specifically around Python internals, OOP, design patterns, and the full stack of a production AI application.

All code is written without AI assistance. Progress is tracked weekly.

Roadmap

• Week 1 — Python foundations + project structure: data structures, comprehensions, generators, dataclasses, FastAPI setup, image upload endpoint.
• Week 2 — Advanced OOP & design patterns: factory, strategy, singleton, hexagonal architecture, dependency injection, Git workflows.
• Week 3 — ML pipeline / Computer Vision: PyTorch tensors, dataloaders, batch inference, U²-Net background removal.
• Week 4 — Async / Celery / Long-running tasks: asyncio, event loop, Celery + Redis, task status tracking.
• Week 5 — Video / Batch processing: OpenCV, ffmpeg, frame extraction, S3 / minIO storage.
• Week 6 — MLOps / Versioning / Tests: MLflow, Pytest, Black / Ruff.
• Week 7 — Containerization / CI: Docker, docker-compose, GitHub Actions, GPU containers.
• Week 8 — Frontend / UX: React, async result display, Stripe quotas.

Weekly Log

Updated every week.