Interactive, text-based courses with hands-on coding environments. No video lectures — learn by doing.
Explore Educative Unlimited →Educative offers a unique approach to technical education: fully interactive, text-based courses where you write and run real code directly in the browser. No setup, no video scrubbing — just focused, hands-on learning at your own pace.
With 500+ courses covering AI, system design, web development, and more, Educative is where 2.9 million developers go to level up. Their AI and agentic systems curriculum is especially strong, with courses on MCP, Google ADK, Claude Code, RAG architectures, and fine-tuning LLMs.
Their Unlimited plan gives you access to every course on the platform, plus AI-powered code feedback, cloud labs, and mock interviews — everything you need to go from learning to building.
Learn to design production-grade autonomous AI systems with multi-agent orchestration, tool use, and reliable decision-making.
Build sophisticated agentic apps using the Model Context Protocol — connect LLMs to tools, data sources, and APIs.
System design interviews focused on generative AI — design RAG pipelines, chat systems, and content generation architectures.
Learn the Model Context Protocol from the ground up — connect AI agents to tools, data sources, and external systems.
Master Claude Code for AI-assisted development — workflows, slash commands, MCP servers, and productivity patterns.
Foundational course covering LLMs, transformers, prompt engineering, and practical generative AI applications.
Build RAG systems from scratch with LangChain — document loaders, embeddings, vector stores, and retrieval chains.
Understand how LLMs work — tokenization, attention mechanisms, training, fine-tuning, and real-world applications.
Comprehensive reference covering the generative AI landscape — models, techniques, tools, and deployment strategies.
Learn the key design patterns for building AI agents — ReAct, chain-of-thought, tool use, planning, and reflection.
Master prompt engineering techniques — few-shot, chain-of-thought, self-consistency, and structured output patterns.
Deep dive into vector databases — embeddings, similarity search, indexing strategies, and production deployment.
Go beyond basic RAG — learn hybrid search, reranking, query transformation, and evaluation frameworks.
Fine-tune large language models efficiently with LoRA and QLoRA — dataset preparation, training, and evaluation.
Build production chatbots combining open-source LLMs with LangChain, Streamlit UI, and agentic RAG patterns.
Combine knowledge graphs with RAG — build graph-enhanced retrieval systems using Neo4j for richer AI responses.
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