PTENES
TRACK 1

🧱 Fundamentals

The foundation of everything. You install Claude Code, understand how it thinks, teach AI to remember your context, and discover the features that multiply your results. By the end, you can use the tool safely.

4
Modules
24
Topics
~3h30
Duration
Beginner
Level
0% 0 of 24
1 · Install 2 · Memory 3 · Power Confident operator

Learning path map

Detailed content

1.1~25 min

🌅 Welcome: imagine and build

The introduction: what Claude Code is, the course mindset, and how to study.

What it is:

Describing it in Portuguese is enough to build software.

Why learn:

The barrier is down; those who understand first get ahead.

Key concepts:

Natural language → code · transferable skill.

What it is:

Treat your ideas as executable projects.

Why learn:

The biggest obstacle is thinking “this isn’t for me.”

Key concepts:

Imagination as specification · you’re the director.

What it is:

A terminal agent that writes, tests, and fixes code.

Why learn:

Prevents false expectations and shows why it outperforms no-code.

Key concepts:

Terminal · coding agent · abstraction layer.

What it is:

Learn by building real things, with a project as the assessment.

Why learn:

Knowledge that becomes a project sticks; loose knowledge evaporates.

Key concepts:

Learn by doing · portfolio · no filler.

What it is:

Three progressive tracks + the Resource Library.

Why learn:

Seeing the map reduces anxiety and helps you choose your pace.

Key concepts:

Fundamentals · Build · Operate & Profit.

What it is:

Sequence, focus, and practice before moving forward.

Why learn:

The small tricks are where the gains come from.

Key concepts:

Sequence · focus · living course.

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1.2~75 min

🛡️ Fundamentals and Setup

Install, understand model×environment, permissions, context, and slash commands.

What it is:

The model is the intelligence; the environment (IDE/terminal) is the armor.

Why learn:

Separating the two avoids confusion when configuring them.

Key concepts:

Model · environment · IDE.

What it is:

Download, authenticate, and open Claude Code.

Why learn:

Proper setup prevents 80% of early problems.

Key concepts:

Download · sign in · first command.

What it is:

Where commands, files, and chat live.

Why learn:

Knowing the interface speeds everything up later.

Key concepts:

Prompt · files · history.

What it is:

How much the agent can do on its own.

Why learn:

Balances speed and security.

Key concepts:

Approve · auto-accept · risk.

What it is:

The AI’s working memory limit per session.

Why learn:

Conversations that are too long make answers worse (context rot).

Key concepts:

Tokens · context rot · clear the session.

What it is:

Commands with “/” and a mode that plans before acting.

Why learn:

Save time and give you control over what gets done.

Key concepts:

/clear · /context · plan mode.

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1.3~45 min

🧠 Memory System

Short-, medium-, and long-term memory—and CLAUDE.md as the project manual.

What it is:

Short (session), medium (project), and long (knowledge base).

Why learn:

Each level solves a different "forgetting" problem.

Key concepts:

Short · medium · long.

What it is:

What fits in the current session—and degrades when it fills up.

Why learn:

Knowing when to clean up maintains quality.

Key concepts:

Session · clear · start over.

What it is:

Separate projects into dedicated folders (5–8 buckets).

Why learn:

Organized context = more accurate answers.

Key concepts:

Folders · scope · 1 manual per folder.

What it is:

A file that explains the project to the AI (≈200 words).

Why learn:

It’s the average memory that isn’t lost between sessions.

Key concepts:

Project manual · short · 1 per folder.

What it is:

A knowledge base that accumulates what matters.

Why learn:

You stop repeating the same context every time.

Key concepts:

Knowledge base · subfolders · accumulation.

What it is:

A routine for saving conclusions in the right folder.

Why learn:

Turns conversation into reusable knowledge.

Key concepts:

Save · correct subfolder · reuse.

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1.4~60 min

⚡ Power features

Slash commands, skills, MCP, and subagents: from solo to turbocharged team.

What it is:

Quick commands that trigger common actions.

Why learn:

Save typing and standardize tasks.

Key concepts:

/command · shortcut · repeatable.

What it is:

How context usage affects cost and quality.

Why learn:

Managing context prevents worse answers and extra costs.

Key concepts:

Tokens · /context · clear.

What it is:

Instruction packages that give AI a ready-made skill.

Why learn:

Reuses expertise without rewriting everything.

Key concepts:

Skill · install · use.

What it is:

A standard for connecting AI to external tools.

Why learn:

Opens the agent to the world (apps, data, APIs).

Key concepts:

Protocol · connector · integration.

What it is:

Several agents working on a task in parallel.

Why learn:

They finish faster and cover more ground.

Key concepts:

Parallel · delegate · orchestrate.

What it is:

One agent produces; another reviews and points out flaws.

Why learn:

Quality improves a lot with adversarial review.

Key concepts:

Create · review · iterate.

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