Develop AI

Build with AI. We point you to the most credible hands-on courses — large language model APIs, agents, fine-tuning and AI integrations — and explain the core concepts behind them. Built for developers and data scientists.

Featured courses

A hand-picked starting point — credible, hands-on courses to build from.

Elements of AI: Building AI

University of Helsinki & MinnaLearn

FreeIntermediate

Claude Code 101

Anthropic

FreeBeginner

Developing LLM Applications with LangChain

DataCamp

PaidIntermediate

Professional Machine Learning Engineer Certification

Google Skills

Advanced

Introduction to Deep Learning with PyTorch

DataCamp

PaidIntermediate

Machine Learning Operations

Databricks

FreeIntermediate

Browse Develop AI by topic

Browse all Develop AI courses or pick an area that matches what you need.

All Develop AI courses

Browse every course on the Develop AI track — filter by topic, level, or provider.

AI Infrastructure & MLOps

Deploy, scale, and monitor AI in production — MLOps and infrastructure for engineers.

Building AI Agents

Wire up tools, memory, and orchestration to build working AI agents — for developers.

Deep Learning

Build and train neural networks — the models behind modern AI, hands-on in code.

LLM & Language AI Development

Build apps on large language models — chatbots, RAG, and semantic search, in code.

Machine Learning Engineering

Build, train, and ship machine learning models — hands-on courses for developers.

Key concepts

The foundational terms these courses build on — start here if you want a quick, plain-English definition first.

Agentic AI AI Agent AI Coding Assistant AI Copilot AI Governance Artificial Intelligence (AI)Attention Mechanism Autonomous Agent Backpropagation ChatGPT Classification Claude Clustering Code Generation Computer Vision (CV)Context Engineering Context Window Data Labeling Dataset Deep Learning Diffusion Model Embeddings Feature Engineering Fine-Tuning Foundation Model Function Calling Gemini Generative AI Gradient Descent Graphics Processing Unit (GPU)Grounding Guardrails Hallucination Human in the Loop Hyperparameter Inference Knowledge Distillation (Distillation)Knowledge Graph Large Language Model (LLM)LLMOps (Large Language Model Operations)Machine Learning Machine Translation MLOps (Machine Learning Operations)Model Context Protocol (MCP)Model Deployment Model Drift Model Monitoring Multi-Agent System Multimodal AI Named Entity Recognition (NER)Natural Language Processing (NLP)Natural Language Understanding (NLU)Neural Network Optical Character Recognition (OCR)Orchestration Overfitting Pretraining Prompt Engineering Pruning Quantization Regression Reinforcement Learning from Human Feedback (RLHF)Responsible AI Retrieval-Augmented Generation (RAG)Semantic Search Small Language Model (SLM)Speech Recognition Speech-to-Text (STT)Supervised Learning Tensor Processing Unit (TPU)Text-to-Image Text-to-Speech (TTS)Text-to-Video Tool Use Training Data Transformer Vector Database Vision-Language Model (VLM)Workflow Automation Zero-Shot Learning

Browse the full AI glossary →