Terminal & Shell
The terminal is where AI engineers live. Get comfortable here. Use piping, redirects, and grep to filter and process training logs from the command line. Create persistent tmux sessions with multiple panes for concurrent training and GPU monitoring. Monitor system and GPU resources with htop, nvtop, and nvidia-smi. Transfer files between local and remote machines using SSH, scp, and rsync. You will spend more time in the terminal than in any editor. Training runs, GPU monitoring, log tailing, remote SSH sessions, environment management. Every AI workflow touches the shell. If you're slow here, you're slow everywhere. This lesson covers the terminal skills that matter for AI work. No history of Unix. No deep-dive into Bash scripting. Just what you need. Three things running at once. One terminal. You can detach, go home, SSH back in, and reattach. The training keeps running. Check which shell you're running: Most systems use bash or zsh. Both work fine. The commands in this course work in either. Key things to know: Piping connects commands together. This is how you process logs, filter output, and chain tools. You will use this constantly. The three redirects you need: Training runs take hours. You don't want to keep your terminal open the whole time. The difference between &, nohup, and screen/tmux: For anything longer than a few…
Terminal & Shell: The terminal is where AI engineers live. Get comfortable here. Use piping, redirects, and grep to filter and process training logs from the…
This free lesson is part of the AI Engineering from Scratch curriculum. Read the full explanation, run the lesson code, and verify the result in the interactive reader or from the repository source.
Browse the complete course catalog or open this lesson on GitHub.