01
Yayasan AI
Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.
Perpustakaan AI gratis
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84 panduan berbahasa Inggris sederhana, jalur pembelajaran terstruktur, dan perpustakaan terbuka — dibuat oleh lembaga nonprofit 501(c)(3) independen sehingga siapa pun dapat memahami AI modern.
84Panduan gratis
1Trek topik
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Five outcome-based courses
Each course includes explicit outcomes, mapped competencies, practice activities, and an applied capstone.
02
Pengguna AI yang bertanggung jawab
Use AI productively while protecting privacy, checking outputs, and preserving human accountability.
03
AI di Tempat Kerja
Evaluate workplace use cases, run safe pilots, measure value, and communicate changes responsibly.
04
Kebijakan & Masyarakat AI
Analyze AI systems through rights, equity, governance, safety, and public-interest outcomes.
05
Membangun dengan Sistem AI
Understand language models, retrieval, agents, evaluation, cost, and deployment safeguards through practical system design.
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Dasar-dasarKonsep inti: cara kerja AI pada tingkat tinggi.84 panduan Bahasa AILLM, NLP, ChatGPT, bisikan, dan pemahaman teks.155 panduan AI visualPembuatan gambar, visi komputer, video, dan desain.133 panduan Audio AISuara, musik, podcasting, dan AI yang mengutamakan audio.117 panduan PerusahaanProfil OpenAI, Anthropic, Google, Meta, dan banyak lagi.121 panduan AplikasiBagaimana AI muncul dalam coding, pencarian, agen, dan kehidupan sehari-hari.111 panduan IndustriAI di bidang kesehatan, keuangan, pendidikan, energi, dan banyak lagi.91 panduan TeknisChip, fine-tuning, RAG, vektor, dan infrastruktur AI.177 panduan MasyarakatBias, privasi, hak cipta, keamanan, dan masa depan AI.30 panduan
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Dasar-dasar
Apa itu AI?
Artificial intelligence (AI) is the field of building computer systems that perform tasks such as recognizing patterns, understanding language, planning…
Dasar-dasarBagaimana AI Belajar
Machine-learning systems learn by adjusting a model using data and a training objective.
Dasar-dasarJaringan Syaraf
A neural network is a machine-learning model made of connected mathematical operations with adjustable parameters.
Dasar-dasarPembelajaran Mendalam
Deep learning is a branch of machine learning that uses neural networks with multiple layers to learn representations of data.
Dasar-dasarPelatihan AI
AI training is the process of adjusting a machine-learning model using examples and a learning objective.
Dasar-dasarInferensi AI
Inference is using a trained model to produce an output from a new input.
Dasar-dasarAI & Data
Data is the recorded information a machine-learning system learns from or processes.
Dasar-dasarModel AI Dijelaskan
A machine-learning model is a mathematical system that maps inputs to outputs using a structure and learned parameters.
Dasar-dasarDasar-dasar Pembelajaran Mesin
Machine learning builds models whose behavior is fitted from examples rather than written entirely as explicit rules.
Dasar-dasarPembelajaran yang Diawasi
Supervised learning fits a model using examples that pair inputs with target outputs.
Dasar-dasarPembelajaran Tanpa Pengawasan
Unsupervised learning looks for structure in data without a target label for every example.
Dasar-dasarAI Generatif
Generative AI produces outputs such as text, images, audio, or code using learned statistical patterns and supplied context.
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