Trust Claude Code with work you don't watch: steer long sessions, enforce rules with hooks, hand jobs off with routines and GitHub, and verify what comes back.
Claude Code can finish a quick task in a single prompt. The hard part is handing it hours
of work, walking away, and trusting what you find when you get back. That gap is what this
course closes. You'll work inside a real project the whole way through, and because
DataCamp provides a ready-to-use environment, you'll run actual Claude Code sessions from
the very first exercise, with no installation or API key required. This course picks up
where an introduction leaves off, so you should already be comfortable running Claude Code
and pointing it at a project.
Steer a Long Session Before It Drifts
Long runs fail quietly, and the fixes are all things you do rather than things you hope
for. You'll scope multi-file work with plan mode, reading the plan and pushing back on it
before a single file changes. You'll direct compaction so the summary keeps the thread you
name instead of whatever Claude picks. You'll use the rewind menu to undo a wrong turn or
compress a long setup phase, set a goal when you can describe "done" more precisely than
the steps, and run parallel sessions in worktrees without them clobbering each other.
Configure Claude So It Actually Follows
Claude follows a lean set of instructions far more reliably than a long one. You'll cut a
bloated CLAUDE.md down to rules specific enough to check, and learn why imports organize a
file without shrinking what loads. You'll package repeated procedures as skills, where the
description is the trigger that makes one fire on its own. You'll match the permission mode
to the job, from hands-on editing to unattended pipelines. And you'll move the rules Claude
must never skip into hooks — code that runs, refusing a push to main outright, or rewriting
a command to strip a live API key while letting the work continue.
Hand the Work Off Entirely
Once you trust Claude with a task, stop doing it by hand. You'll schedule prompts as
routines that run on Anthropic's infrastructure with nothing for you to host, and learn the
guardrails that make an autonomous run safe to leave alone. You'll drop to headless mode
when a job needs your own pipeline, shaping output to a JSON schema so the next script can
read it. You'll see where the Agent SDK fits when the work belongs inside your own
application, and put Claude on pull requests with managed Code Review and the GitHub
action.
Verify What Came Back, Then Share It
A run nobody watched needs a real check, not a tidy summary. You'll read the diff rather
than the write-up, and see why a clean summary can sit on top of a change nobody asked for.
You'll gate the end of a turn on a real type check with a Stop hook, so Claude cannot finish
on a broken build. You'll get a cold second opinion from a session with no memory of how the
code was written. Finally you'll package the setup you trust — skill, hooks and all — as a
plugin your whole team installs in one step.
By the end you'll be able to point Claude Code at hours of work, walk away, and check the
result with confidence.
Steer long sessions with plan mode, directed compaction, the rewind menu, goals, and worktrees, so hours of work stay on track instead of drifting.
Write a lean CLAUDE.md with rules specific enough to check, and package the procedures you repeat as skills that fire without being asked.
Enforce limits Claude cannot skip by matching the permission mode to the job and moving hard rules into hooks that block or rewrite a tool call.
Automate repeat work by choosing between routines, headless mode, and the Agent SDK, then putting Claude to work on pull requests with the GitHub action.
Verify a run nobody watched with the diff, a Stop hook, and a cold second opinion, then package the setup you trust as a plugin.
A long session drifts unless you shape it. Scope the work with plan mode, direct compaction so the summary keeps what matters, use the rewind menu to course-correct, set a goal when you can describe done better than the steps, and run parallel work in worktrees.
Claude follows a lean set of instructions far more reliably than a long one. Write a CLAUDE.md that survives contact with a real project, package repeated procedures as skills, match the permission mode to the job, and move the rules Claude must never skip into hooks.
Once you trust Claude with a task, stop doing it by hand. Schedule prompts as routines on Anthropic's infrastructure, drop to headless mode when the job needs your own pipeline, and put Claude to work on pull requests with managed code review and the GitHub action.
A run nobody watched needs a real check, not a tidy summary. Read the diff yourself, gate the turn on tests with a hook, get a cold second opinion on anything that matters, then package the setup you trust as a plugin your whole team can install.
Some, yes. This course assumes you have already run Claude Code, pointed it at a project, and written or edited a CLAUDE.md. It does not re-explain what a coding assistant is or how tool use works. If you are starting from scratch, take the introductory Claude Code course first, then come back for the workflows that make longer, less supervised work reliable.
What topics does this course cover?
Scoping long sessions with plan mode, directing compaction, using the rewind menu, setting goals, and running parallel work in worktrees. Writing a CLAUDE.md Claude actually follows, packaging procedures as skills, choosing the right permission mode, and enforcing hard rules with hooks. Handing work off with routines, headless mode, the Agent SDK, managed Code Review, and the GitHub action. Then verifying unsupervised runs by reading the diff, gating the turn on real checks, and getting a cold second opinion — and packaging the whole setup as a plugin.
Where can I use this after completing the course?
Anywhere you write code. Claude Code lives in your terminal and integrates with the tools you already use — VS Code, JetBrains, Claude Desktop, and the web. More to the point, every technique here is built to transfer: the CLAUDE.md standards, the skills, the hooks, the permission-mode choices, the routines and GitHub workflows, and the verification habits all drop straight into your own repositories, not just the course sandbox.
Is this course free to take?
Yes. This course can be completed from beginning to end without a paid DataCamp subscription.
What does this cover that an introductory course doesn't?
Introductions cover getting good results while you are watching. This course is about the work you are not watching: enforcing rules in code rather than requesting them, matching permission modes to unattended runs, scheduling and triggering Claude without a human present, and verifying the output of a run that nobody supervised. It ends where most courses stop — packaging your setup as a plugin so a whole team inherits it.
After doing these courses, I feel confident creating professional visualizations and dashboards
For someone without a strong programming background, DataCamp was really beginner-friendly. You watch some videos and then practice immediately - I was able to learn fast
Ebuka NwafornsoGraduate Student, University College Dubllin
DataCamp is a cost-effective way to upskill and stay relevant with data and AI. It’s structured, practical, and lets you apply what you learn immediately
Raul RomeroProduct Manager III, Ebay
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