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Advanced programming requiremetns

Original OneNote page: **Project Tracker - Advanced programming requiremetns **

Route: product/technical note to route

Categories: product_technical_or_learning

Source

  • Word export: C:\Users\adeel\OneDrive\100_Knowledge\203_TextCAD\01_Product_Project_Management\TextCAD_Wiki\inbox\onenoteexport\01_PROJECTS\Gauss Compute\Project Tracker - Advanced programming requiremetns .docx
  • MHT export: C:\Users\adeel\OneDrive\100_Knowledge\203_TextCAD\01_Product_Project_Management\TextCAD_Wiki\inbox\onenoteexport\01_PROJECTS\Gauss Compute\Project Tracker - Advanced programming requiremetns .mht

Extracted Notes

These notes are extracted from the Word export so the source is visible in the wiki without moving or deleting the original file.

  • Advanced programming requiremetns
  • Nice — this is a great, realistic question and you’re asking the right thing: focus. Below I give a single, prioritized learning roadmap that covers both AI engineering (models, pipelines, serving, MLOps) and solid software engineering (OOP, architecture,...
  • Short summary (one line)
  • Focus first on advanced Python fundamentals + software engineering practices, then layer data/ML fundamentals → model tooling & inference → model serving & MLOps, and in parallel learn the integration & UI tech you’ll use to build the app and connect to CAD...
  • Must-learn topics (priority order)
  • These are the essentials you should already or soon be comfortable with.
  • Core advanced Python (essential)
  • OOP & design: classes, inheritance, composition, SOLID principles, dependency injection.
  • Type hints & static typing: typing, mypy.
  • Iterators / generators / comprehensions and lazy evaluation.
  • Context managers & resource management (with, enter/exit).
  • Decorators & higher-order functions.
  • Concurrency & parallelism: threads, asyncio, process pools, concurrent.futures.
  • Memory & performance basics: profiling, cProfile, timeit, numpy vectorization.
  • Packaging & distribution: setuptools/poetry, virtualenv, packaging for desktop (PyInstaller, briefcase/Tauri options).
  • Testing & quality: pytest, unit/integration tests, mocking, linters (flake8/ruff), formatters (black).
  • Software engineering + systems (essential)
  • Architecture patterns: layered, hexagonal/clean architecture, microservices vs monolith tradeoffs.
  • APIs: REST (FastAPI/Flask), gRPC basics.
  • Databases: SQL basics + ORM (SQLAlchemy) and NoSQL when needed.
  • Version control & CI/CD: Git fluency, GitHub Actions / GitLab CI, basic pipeline creation.
  • Containers & infra: Docker, basic Kubernetes concepts (pods, services) — at least enough to deploy models.
  • Logging & monitoring: structured logs, Prometheus / Grafana basics (or hosted alternatives).
  • Data & ML foundations (essential for AI engineering)
  • Math basics: linear algebra (vectors/matrices), probability, gradients/intuitions for optimization.
  • Data handling: pandas, numpy, data cleaning & feature engineering.
  • ML basics: supervised learning workflows, evaluation metrics, overfitting/regularization.
  • Deep learning frameworks: PyTorch (preferred for modern research/engineering) — model building, training loop, saving/loading.
  • Transformers / language models: architecture intuition, using Hugging Face transformers, tokenization, fine-tuning vs prompt-based use.
  • Model deployment & LLM/AI-tooling (essential for production)
  • Model serving: FastAPI + uvicorn, TorchServe or Triton basics, or model servers like BentoML/Ray Serve.
  • Embeddings & vector search: embeddings + vector DBs (Pinecone, Weaviate, Milvus, or a self-hosted option).
  • Prompt engineering & evaluation: constructing, testing, and automating prompts; guardrails and prompt templates.
  • MLOps: experiment tracking (Weights & Biases), model versioning (DVC or MLflow), automated retraining pipelines.
  • Optimization for inference: quantization, batching, GPU vs CPU tradeoffs.

URLs Found

  • https://chatgpt.com/g/g-p-689b4dd612f4819191e700de385217ce/c/68f8d409-64f8-8328-a0ce-fc105374341c

Next Curation Action

Review for Product Wiki migration. Keep only relationship, GTM, or CRM implications in the Network Wiki.

Sources

  • C:\Users\adeel\OneDrive\100_Knowledge\203_TextCAD\01_Product_Project_Management\TextCAD_Wiki\inbox\onenoteexport\01_PROJECTS\Gauss Compute\Project Tracker - Advanced programming requiremetns .docx
  • C:\Users\adeel\OneDrive\100_Knowledge\203_TextCAD\01_Product_Project_Management\TextCAD_Wiki\inbox\onenoteexport\01_PROJECTS\Gauss Compute\Project Tracker - Advanced programming requiremetns .mht