Language AI courses and concepts
Language AI is the branch of artificial intelligence that works with human language: understanding and generating text, translating between languages, and converting speech to text and text to speech. Most modern language models split text into small pieces called tokens, represent each piece as numbers, and learn from large amounts of text how those pieces relate to each other. This lets them produce fluent text, but fluent text is not always accurate, so their output still has to be checked. Learning the subject means understanding that process first, then the specific tasks built on it, such as translation, sentiment analysis and speech recognition.
Language AI courses
Learn AI — how language models work, without code
Use AI — language services and everyday tools
AI Tools for Accountants
Learnsignal
Amazon Lex Getting Started
AWS Skill Builder
Amazon Polly Getting Started
AWS Skill Builder
Amazon Transcribe Getting Started
AWS Skill Builder
Build Your First Chatbot
IBM SkillsBuild
Machine translation in language learning and teaching
The Open University
Natural Language Processing for Accountants
Learnsignal
Develop AI — build language models and applications in code
Building Language Models on AWS
AWS Skill Builder
Develop natural language solutions in Azure
Microsoft Learn
Get started with AI applications and agents on Azure
Microsoft Learn
Google DeepMind: AI Research Foundations
Google Skills
LLM University
Cohere
Rapid Application Development with Large Language Models (LLMs)
NVIDIA Deep Learning Institute
Language AI terms explained
Most of these terms fall into three groups: tasks (machine translation, sentiment analysis, named entity recognition, speech recognition, text-to-speech), the building blocks language models work with (tokens, tokenization, word embeddings), and the systems people talk to (chatbots, conversational AI, voice AI). Token and tokenization explain how much text a model can take in at once, and why usage is counted in tokens rather than words.
Learn AI covers how AI systems work, including the machine learning that language models are built on; Use AI covers using AI tools and services, for language tasks and others; Develop AI covers building with AI in code, including applications on top of language models.