{"id":33345855,"url":"https://github.com/msg-careerpaths/node-ai-training","last_synced_at":"2026-04-15T14:06:15.808Z","repository":{"id":324681514,"uuid":"1097814094","full_name":"msg-CareerPaths/node-ai-training","owner":"msg-CareerPaths","description":"This is the official Node AI Training for .msg Career Paths","archived":false,"fork":false,"pushed_at":"2025-11-17T08:35:19.000Z","size":477,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-11-17T10:21:20.786Z","etag":null,"topics":["angular","aws","aws-bedrock","langchain-js","nestjs","prompt-engineering","rag","typescript","vector-database"],"latest_commit_sha":null,"homepage":"","language":"TypeScript","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/msg-CareerPaths.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-11-16T21:36:43.000Z","updated_at":"2025-11-17T08:35:23.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/msg-CareerPaths/node-ai-training","commit_stats":null,"previous_names":["msg-careerpaths/node-ai-training"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/msg-CareerPaths/node-ai-training","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/msg-CareerPaths%2Fnode-ai-training","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/msg-CareerPaths%2Fnode-ai-training/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/msg-CareerPaths%2Fnode-ai-training/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/msg-CareerPaths%2Fnode-ai-training/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/msg-CareerPaths","download_url":"https://codeload.github.com/msg-CareerPaths/node-ai-training/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/msg-CareerPaths%2Fnode-ai-training/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":285737153,"owners_count":27223129,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-11-22T02:00:05.934Z","response_time":64,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["angular","aws","aws-bedrock","langchain-js","nestjs","prompt-engineering","rag","typescript","vector-database"],"created_at":"2025-11-22T05:00:36.646Z","updated_at":"2025-11-22T05:01:30.998Z","avatar_url":"https://github.com/msg-CareerPaths.png","language":"TypeScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Node AI Training\n\n\u003e\n\u003e Note this training assumes you have some previous experience with `Angular`, `Nest.js` and `AWS`.\n\u003e\n\u003e If you do not, please consult those training paths beforehand.\n\u003e\n\n## Mandatory Content\n\n- Introduction\n  - [0.0 Introduction](./chapters/000-introduction/000-introduction.md)\n  - [0.1 Foundational Theory](./chapters/000-introduction/001-foundational-theory.md)\n- Prompt Engineering and Integration\n  - [1.0 Introduction](./chapters/100-prompt/100-prompt-intro.md)\n  - [1.1 Prompt Integration](./chapters/100-prompt/101-prompt-integration.md)\n  - [1.2 Prompt Strategies](./chapters/100-prompt/102-prompt-strategies.md)\n  - [1.3 Prompt Context](./chapters/100-prompt/103-prompt-context.md)\n  - [1.4 Prompt Tooling](./chapters/100-prompt/104-prompt-tooling.md)\n  - [1.5 Prompt Evaluations](./chapters/100-prompt/105-prompt-evaluations.md)\n- Chat and Streaming\n  - [2.0 Chat LLM Streaming](chapters/200-chat/200-chat-llm-streaming.md)\n- Retrieval Augmented Generation (RAG)\n  - [3.0 RAG Intro](./chapters/300-rag/300-rag-intro.md) \n  - [3.1 RAG Theory Vectors and Embeddings](./chapters/300-rag/301-rag-theory-vectors-and-embeddings.md) \n  - [3.2 RAG Document Vectors and Parsing](./chapters/300-rag/302-rag-document-vectors-and-parsing.md) \n  - [3.3 RAG Structured Extraction](./chapters/300-rag/303-rag-structured-extraction.md)\n- Agent Orchestration\n  - [4.0 Agent Orchestration Intro](./chapters/400-agent-orchestration/400-agent-orchestration-intro.md)\n- Model Context Protocol (MCP)\n  - [5.0 MCP Intro](./chapters/500-mcp/500-mcp-intro.md)\n\n## Training App\n\nThe training provides a sample application you will use to integrate LLM functionalities into it. 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