AI Foundations
Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.
Ücretsiz AI kütüphanesi
1019 Herkesin modern yapay zekayı anlayabilmesi için bağımsız bir 501(c)(3) kar amacı gütmeyen kuruluşu tarafından oluşturulmuş sade İngilizce kılavuzlar, yapılandırılmış öğrenme yolları ve açık bir kütüphane.
Buradan başlayın
Each course includes explicit outcomes, mapped competencies, practice activities, and an applied capstone.
Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.
Use AI productively while protecting privacy, checking outputs, and preserving human accountability.
Evaluate workplace use cases, run safe pilots, measure value, and communicate changes responsibly.
Analyze AI systems through rights, equity, governance, safety, and public-interest outcomes.
Understand language models, retrieval, agents, evaluation, cost, and deployment safeguards through practical system design.
Konu parçaları
İlgilendiğiniz alana atlayın. Her parçanın birden fazla sade İngilizce kılavuzu vardır.
Tam kütüphane
1019 arasında 1019 gösterilen kılavuzlar. Parçaya göre filtreleyin veya yukarıda arayın.
AI customer service systems answer questions, classify requests, summarize conversations, and propose resolutions.
UygulamalarAI in HR can help organize applications, schedule interviews, summarize feedback, or support workforce planning.
EndüstrilerAI in agriculture can support crop monitoring, disease detection, yield forecasting, irrigation, and farm logistics.
EndüstrilerAI in manufacturing can inspect products, predict maintenance, plan production, and optimize processes.
EndüstrilerAI in retail can forecast demand, personalize discovery, detect fraud, optimize inventory, and assist shoppers.
EndüstrilerAI in logistics can forecast demand, route vehicles, estimate arrival times, inspect shipments, and coordinate warehouses.
EndüstrilerAI in real estate can estimate prices, match properties, process documents, forecast maintenance, and support transactions.
TeknikFine-tuning continues training an existing model on a selected dataset or objective.
TeknikRetrieval-augmented generation, or RAG, supplies retrieved material to a generative model when answering a request.
TeknikA vector database stores numerical representations and retrieves records using a similarity measure, often alongside metadata filters.
TeknikEdge AI runs model processing close to where data is collected or used, such as on a phone, camera, vehicle, or local gateway.
TeknikQuantum AI describes intersections between quantum computing and machine learning, such as using quantum circuits in learning algorithms or using machine…
Check what you learned with topic quizzes, then explore our structured courses and current certification requirements. Core guides remain free to read.