Für Fachinformatiker/Inen für Daten und Prozessanalyse nach neuem Katalog (2025)
Übersichet aller neuen bzw. GECHTRICHENE Themen
Diese Tabellen stammen aus Noel Langs YT Video.
(§ 4 Abs. 2 Nr. 2)
Für Fachinformatiker/Inen für Daten und Prozessanalyse nach neuem Katalog (2025)
Übersichet aller neuen bzw. GECHTRICHENE Themen
Diese Tabellen stammen aus Noel Langs YT Video.
(§ 4 Abs. 2 Nr. 2)
| #!/usr/bin/env bash | |
| parse_ini() { | |
| local ini_file="$1" | |
| # declare -A config | |
| current_section="" | |
| while IFS= read -r line; do | |
| line=$(echo "$line" | sed -e 's/^[ \t]*//;s/[ \t]*$//') | |
| if [[ "$line" =~ ^\; ]] || [[ -z "$line" ]]; then | |
| continue |
| # .claude-ignore - Files and directories to exclude from Claude Code analysis | |
| # Place this in your Magento 2 project root directory | |
| # Vendor Dependencies (too large and not project-specific) | |
| /vendor/ | |
| /node_modules/ | |
| # Generated and Cache Files | |
| /var/ | |
| /generated/ |
| name | ASD-STE100 |
|---|---|
| description | Simplified Technical English — one meaning per word, active voice, simple tense, short sentences, small noun clusters. |
| keep-coding-instructions | true |
You are an interactive CLI tool that helps users with software engineering tasks.
Write all English in ASD-STE100 Simplified Technical English. STE is a controlled language. The aerospace industry built it so that a reader who cannot ask a follow-up
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| #!/usr/bin/env bash | |
| # | |
| # oas2nginx.sh (c) NGINX, Inc. [v0.5 13-Jan-2020] Liam Crilly <liam.crilly@nginx.com> | |
| # | |
| # Converts OpenAPI/Swagger spec into nginx.conf snippet (server context) as per | |
| # https://www.nginx.com/blog/deploying-nginx-plus-as-an-api-gateway-part-1/ | |
| # Requires shyaml for YAML processing: https://github.com/0k/shyaml | |
| # Defaults | |
| # |
Audit this entire codebase for materially useful simplifications in its data structures, state representation, control flow, algorithms, and ownership.
This is an audit-only exercise. Do not edit files, run tests, implement recommendations, commit, or push. Read-only inspection commands are allowed.
You are the coordinator. Continue until the complete codebase has been reviewed and the final audit is validated.
Inspect the repository and inventory every identifiable subsystem.
| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <title></title> | |
| <meta charset="utf-8" /> | |
| <script src="Scripts/jquery-1.9.1.min.js"></script> | |
| <link href="Content/bootstrap.min.css" rel="stylesheet" /> | |
| <script src="Scripts/isRockFx.js"></script> | |
| <script> | |
| $(function () { |
how to leverage oracle's temping offers
The limits of the free tier say that you can create up to 4 instances.
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