Barcha yo'l xaritalari

AI muhandisi

2026-yilda AI engineer bo'lish uchun bosqichma-bosqich qo'llanma

0% tugallandi0 / 190 mavzu
AI engineer kim?

AI engineer user experience'ni yaxshilash uchun pre-trained modellar va mavjud AI vositalaridan foydalanadi. U modellarni noldan yaratmasdan, AI'ni amaliy maqsadlarda qo'llashga e'tibor qaratadi. Shu jihati bilan u ko'proq yangi modellar yaratish yoki AI nazariyasini rivojlantirish bilan shug'ullanadigan AI researcher'lar va ML engineer'lardan farq qiladi.

Hugging Face
Dastlabki talablar (ulardan biri)
Scrimba o'zining AI Engineer kursiga 20% chegirma taklif qilmoqda. Ko'rib chiqing!
AI Engineer
Kirish
AI engineer kim?
AI engineer va ML engineer
Large Language Model (LLM)
Inference
Training
Vector DBs
RAGs
Prompt Engineering
AI Agents
AI va AGI
Asosiy atamalar
Frontend
Backend
Full-Stack
Mahsulot ishlab chiqishga ta'siri
Rollar va mas'uliyatlar
Pre-trained Models
Token'lar
Context
Anthropic Claude
Google Gemini
OpenAI (GPT, o-series)
Meta Llama
Mistral
Cohere
LLM'lar qanday ishlaydi
ReAct
CoT
Zero-Shot
Top-K
Top-P
Few-Shot
Prompt Engineering
AI safety va etika
AI safety muammolarini tushunish
Prompt Injection Attacks
Bias va fairness
Xavfsizlik va maxfiylik muammolari
Adversarial testing o'tkazish
Content Moderation APIs
Prompt'larga end-user ID'larini qo'shish
Robust prompt engineering
Mijozlar va use case'larni biling
Kirish va chiqish ma'lumotlarini cheklash
Xavfsizlik bo'yicha eng yaxshi amaliyotlar
LM Studio
Closed va open source modellar
Hugging Face Hub
Hugging Face Inference SDK
Transformers.js
Ollama
OpenAI Response API
Google Gemini APi
Embedding'lar nima?
Semantic Search
Recommendation Systems
Anomaly Detection
Data Classification
Embedding use case'lari
Open AI Embeddings API
Cohere
Gemini Embedding
Jina
Sentence Transformers
Hugging Face'dagi modellar
Vector Databases
Maqsadi va imkoniyatlari
Chroma
Pinecone
Weaviate
FAISS
LanceDB
Qdrant
Supabase
MongoDB Atlas
Mashhur Vector DB'lar (birini tanlang)
Embedding'larni indekslash
Similarity search'ni bajarish
Vector search'ni amalga oshirish
RAG nima?
RAG use case'lari
RAG va fine-tuning
Chunking
Embedding
Vector Database
Retrieval Process
Generation
RAG'ni amalga oshirish
RAG'ni amalga oshirish usullari
SDK'lardan bevosita foydalanish
Langchain
Llama Index
Tool'lar va function calling
DeepSeek
AI Agents
Agents Usecases
AI Agents
ReAct Prompting
Qo'lda amalga oshirish
OpenAI AgentKit va Agent SDK
Claude Agent SDK
AI agent'lar yaratish
Multimodal AI
Multimodal AI use case'lari
Image Understanding
Image Generation
Video Understanding
Audio Processing
Text-to-Speech
Speech-to-Text
Multimodal AI vazifalari
OpenAI Vision API
DALL-E API
Whisper API
Hugging Face Models
Multimodal ilovalar uchun LangChain
Multimodal ilovalar uchun LlamaIndex
Multimodal AI'ni amalga oshirish
Quyidagi tegishli yo'nalishlar bilan o'rganishni davom ettiring
Forward Deployed Eng.
Prompt Engineering
Development Tools
Scrimba - AI Engineer yo'li
Tegishli yo'l xaritalari
  • Vibe Coding
  • Claude Code
  • Prompt Engineering
  • Inference Engineering
  • Forward Deployed Engineer
LLM'ning asosiy elementlari
Haystack
RAGFlow
Inference Engineering
Model Context Protocol (MCP)
MCP Host
MCP Server
Asosiy component'lar
MCP Client
Data Layer
Transport Layer
MCP server yaratish
MCP bilan dasturlash
MCP client yaratish
Lokal serverga ulanish
Masofaviy serverga ulanish
Vertex AI Agent Builder
Google ADK
Ushbu yo'l xaritasining batafsil versiyasini va boshqa shunga o'xshash yo'l xaritalarini toping
roadmap.sh
Fine-tuning
LLM'lar bilan ishlash
Inference Engineering
Prompt Engineering
Input Format
System Prompting
Context
Rol va xulq-atvor
Cheklovlar
Structured Output
Function Calling
Prompt Caching
Streaming Responses
Model turlari
Closed modellar
AI modellari
Self-Hosted Models
Repetition Penalties
To'g'ri modelni tanlash
Open source modellar
Gemma
Qwen
Platformalar va ekotizim
OpenRouter
Embedding Models
Proprietary modellar
Open source modellar
API va SDK'lar
Claude Messages API
OpenAI-compatible APIs
Embedding'lar va vector database'lar
RAG
AI agent'lar
Multi-agents
Hugging Face Tasks
Embeddings
AI safety va etika
AI'ning boshqa qo'llanilishlari
Claude Code
Gemini
Codex
OpenCode
Cursor
Replit
AI yordamida kod yozish vositalari
NanoBanana API
Sampling Parameters
Temperature
RAG va dynamic filter'lar
Context Compaction
Context Isolation
Vibe Coding
Evaluation va observability
LLM Observability
LLM Evaluations
Tracing va logging
Xarajat/latency monitoringi
Production monitoring
Observability vositalari
LangSmith
Langfuse
Helicone
Arize AI
Deterministic Evals
Model-Based Evals
Human Evals
Evaluation Metrics
Regression Testing
Evaluation turlari
Evaluation vositalari
DeepEval
RAGAS
Context Engineering
Prompting usullari
Prompt tuzilishi
Model bilan ishlash
Context va prompt eng.
Context Sources
Context Window
Asoslar
MCP
Multi-agent Context Sharing
Context Evaluation
Context Security
Context engineering usullari
Context layer nima?
Long-Context Processing
State va tarixiy kontekst
Context Failure Modes
Vositalar va context warehouse'lar
PostHog
modus
Atlan
Memory Systems
DataHub
Context Engineering

Ko'p so'raladigan savollar

Yo'l xaritalariQo'llanmalarFAQYouTube

yo'lxaritaroadmap.shasosida

Hamjamiyat tomonidan yaratilgan yo'l xaritalari, eng yaxshi amaliyotlar, loyihalar, maqolalar, manbalar va yo'nalishlar — o'z yo'lingizni tanlash va kasbingizda o'sish uchun.

© yo'lxarita·Shartlar·Maxfiylik·

roadmap.sh

Barcha kontent roadmap.sh loyihasidan olingan (© Kamran Ahmed) va shaxsiy o'rganish uchun o'zbek tiliga tarjima qilinmoqda.

Asl sayt·GitHub

Qidiruv

Yo'l xaritalari, loyihalar va savollarni qidiring