🤖 Free course

FitXpert: 230-Day AI Engineering Roadmap

One product, eight modules — backend engineer to production AI platform engineer.

A day-by-day path from Python and classical CV through deep learning, LLM engineering, generative fine-tuning, AI system design, and inference optimization — building one product, FitXpert, a virtual trial room for apparel retail, one module at a time.

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S0 · Days 1–14

Python + Classical CV — the Catalog Tool

Python idiom, NumPy, Pandas, and OpenCV — ending with an auto-cleanup pipeline for garment photos, deployed as an endpoint.

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S1 · Days 15–45

ML → Deep Learning via PyTorch — the Garment Classifier

Classical ML vocabulary, backprop from scratch (micrograd), PyTorch fundamentals, and CNNs — ending with a served, ≥90%-accurate classifier.

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S2 · Days 46–90

CV Depth: the Measurement Pipeline

Detection, pose, segmentation, and human parsing as one production pipeline — ending in a size recommendation validated with a tape measure.

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FitXpert: 230-Day AI Engineering Roadmap

Foundations — CV EngineerDays 1–90Python, deep learning, and the full Measurement Pipeline. Day-90 off-ramp: interviewable for CV-flavored AI Engineer roles.0/90

AI Platform EngineerDays 91–210LLM engineering, generative fine-tuning, AI system design, and inference optimization — the profile most AI Engineer / AI Platform / Inference Infrastructure roles hire for.0/120

GPU Systems (optional)Days 211–230One honest CUDA kernel and per-kernel profiling literacy — recommended, not required, differentiation.0/20

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