Seven ready paths for different roles and goals. Each includes a course sequence, expected outcome, and time estimate.
Beginner8 h
A foundational track for those encountering large language models for the first time. After it, you understand how LLMs are built, can phrase prompts, and solve real tasks in ChatGPT/Claude/Gemini.
Who it's for: Beginners with no AI experience
Outcome: You confidently use the main assistants for text, finding information, transcripts, everyday tasks. You know the model's limits and don't trust it blindly.
Intermediate12 h
A track for founders and executives. The focus is on how AI removes routine, speeds up operations, and replaces part of your contractors. No hype: only what's applicable in business.
Who it's for: Founders, CEOs, operations directors
Outcome: You understand which tasks in your business can be handed to an LLM right now. You roll out assistants to the team, work out the economics, and don't waste budget on unnecessary integrations.
Intermediate16 h
A track for engineers. It teaches you to write production code with Claude Code, Codex, Cursor, and Windsurf, build agents, and connect models to external systems via MCP and tools.
Who it's for: Developers, tech leads, platform engineers
Outcome: You use AI coding tools in real work, build simple agents with tool use, connect MCP servers, and understand when RAG is needed and when a long context is enough.
Intermediate10 h
A track on applying AI to content, outreach, competitor analysis, and lead work. Includes hands-on LinkedIn practice, email campaigns, and pipelines in n8n.
Who it's for: Marketers, sales, growth teams
Outcome: You launch content pipelines and outreach campaigns, enrich lead databases, prepare personalized messages, and see numbers, not 'the vibe'.
Intermediate12 h
A track on how to assemble working automations in which an LLM is one of the nodes. n8n, Make, Zapier, webhooks, queues, agents with tools.
Who it's for: Operations, RevOps, solopreneurs, technical marketers
Outcome: You design and maintain automations in which an LLM solves a concrete task — classification, extraction, generation — and doesn't eat the budget.
Advanced14 h
An advanced track on agents: tool use, planning, multi-agent systems, MCP, evaluation and failures. For those who have already tried it and want to get it to production.
Who it's for: Senior engineers, AI engineers, R&D
Outcome: You build agents that do useful work without constant hand-holding. You understand where they break and how to catch it.
Intermediate10 h
A track on a private AI stack. Running models locally via Ollama and LM Studio, choosing hardware, working with documents via RAG, open-source models.
Who it's for: Engineers, privacy-sensitive teams, the legal/medical segment
Outcome: You stand up local models, understand the trade-offs between quality and privacy, and build RAG over your own documents.
Intermediate6 h
Track for everyone who wants to use AI responsibly: risks, privacy, bias, and regulations.
Who it's for: All professionals working with AI
Outcome: Understanding AI risks, protecting data, and evaluating the ethics of AI solutions.