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Core Python language — variables, functions, OOP, data structures, and beyond

NumPy, Pandas, Matplotlib, scikit-learn, and the Python data stack

ML concepts, model training, deep learning, NLP, and computer vision

ML deployment, monitoring, pipelines, GPU computing, model serving, and distributed training

Agent frameworks, LangChain, orchestration patterns, and autonomous workflows

Claude models, API, prompting techniques, styles, projects, and connectors

Hooks, skills, plugins, MCP, IDE integrations, worktrees, and enterprise patterns

Installation, configuration, security, and production deployment of OpenClaw

n8n workflows, AI agents, and automation platform patterns

Docker, GitHub Actions, testing, Terraform, and deployment pipelines