Claude Ustalığı
Learn from scratch what Claude is, how it differs from traditional chatbots, and how it will reshape your daily workflow.
How this learning category is structured
Each category is a progressive chain of modules — from foundational concepts to production-grade architectural choices. Following the sequence is faster, but every module is self-contained.
Module shape is consistent: a short text/video lesson (10–15 minutes), a hands-on example (code + data), a 10–15 question assessment, and a real-world use case anchor. This structure forecloses the 'I saw it, I get it' trap — the assessment-after-application tests whether the concept actually moved into working memory.
Each category emphasizes production-grade practice: in prompt engineering, not just prompt templates but prompt versioning and A/B testing; in RAG, not just chunk-and-embed but hybrid retrieval + reranker + evaluation; in LLMOps, not just deployment but observability and cost attribution.
Recommended path: complete foundational modules in order first, then selectively consume advanced modules based on need. If you prefer cohort format, drip-release paces you with peers; in self-paced mode you control the cadence.
- Each module: 10–15 minute lesson + hands-on example + assessment.
- Production-oriented; lessons anchor in real vendor/tooling choices.
- Modules are independently consumable, but the sequence accelerates retention.
- Pro membership unlocks certificate exam + AI tutor + drip cohort access.
Table of Contents
1. Foundations — Welcome to Claude
- 1
What is Claude? The New Generation of AI Assistants
Learn from scratch what Claude is, how it differs from traditional chatbots, and how it will reshape your daily workflow.
- 2
Anthropic, Constitutional AI and Safety Philosophy
Understand Constitutional AI, Anthropic's safety philosophy, and the reasoning behind what Claude refuses to do.
- 3
Meet the Models: Opus, Sonnet, Haiku Compared
Learn the strengths, costs, and speed of Claude's three main models (Opus, Sonnet, Haiku) and which one to pick in each scenario.
- 4
Your First Conversation: Web, Mobile, and Desktop Tour
Tour every corner of Claude.ai web, mobile, and desktop apps; master Projects, Artifacts, and keyboard shortcuts from day one.
- 5
Claude's Capability Map and Limits
See where Claude shines and where it struggles on a clear capability map — covering hallucination, fresh data, and complex math.
2. Prompt Engineering Foundations
- 1
Clarity and Specificity: From Vague to Surgical Prompts
Vague prompts produce vague answers. Learn to surface the true intent under fuzzy requests and acquire surgical specificity.
- 2
Structured Prompts with XML Tags
Make your prompts parseable, maintainable, and testable using the XML tags pattern Anthropic recommends.
- 3
Designing and Versioning Prompt Templates
Production prompts should be treated like code: templates, parameters, versions, tests, and monitoring. Learn to manage them with software-grade discipline.
3. Advanced Prompting Techniques
- 1
System Prompt and Persona Design
How do you design Claude's personality, boundaries, and behavior frame via the system prompt? Production-ready persona patterns inside.
- 2
Output Format Control: JSON, Markdown, Tables
Master three techniques to keep Claude's output parseable, consistent, and error-free: schema, prefill, and validator-loop.
- 3
Multi-Step Task Decomposition
Instead of solving complex tasks in one prompt, break them into modular subtasks for better accuracy, testability, and cost.
- 4
Prompt Debugging: Why Isn't This Working?
Prompt not working? Learn a systematic diagnostic tree, logging strategy, and model swap checklist.
- 5
Token Economy and Cost Optimization
Produce the same quality at 50-90% lower cost using token economy: prompt caching, model tiering, output constraints, batching.
4. Coding with Claude
- 1
Generating Functions and Classes from Scratch
Workflow for producing production-ready functions/classes from a clear spec with Claude: signature, edge cases, tests, docs.
- 2
Code Review, Refactor, and Optimization
Use Claude as a code reviewer: pattern detection, refactor suggestions, performance tuning, and security review.
- 3
Bug Hunt: From Stack Trace to Fix
Workflow for systematically finding a bug with Claude: minimum repro, hypothesis, isolation, fix, regression test.
- 4
Test Writing, TDD, and Coverage Strategies
Workflow for writing tests with Claude: unit, integration, property-based, snapshot. Coverage targets and which tests not to write.
- 5
Documentation, Docstrings, and README Generation
Generate docstrings, READMEs, ADRs, runbooks with Claude. Turn docs from a debt into a revenue-producing asset.
- 6
Claude Code: Working in the Terminal
Claude in the terminal via Claude Code CLI — project mapping, file editing, code execution, hooks, and plan mode.
5. Creative and Professional Writing
- 1
Blog, Article, and Long-Form Content
From a topic seed to a 2,000-4,000-word quality long-form piece with Claude — including SEO, tone, and originality.
- 2
Emails, Briefs, and Business Correspondence
Cold sales emails, customer save, bad-news memos, briefs — proven prompt patterns for every kind of business writing.
- 3
Story, Script, and Character Development
Fundamentals of character, conflict, scene, and dialogue + ethics of creative writing with Claude. From novel design to short-film scripting.
- 4
Translation, Localization, and Style Consistency
Beyond word-for-word — cultural adaptation, brand voice, terminology memory, and QA cycle. Focus on Turkish-English.
- 5
Preserving Voice and Tone: Style Transfer
Transferring written voice to Claude — generating consistent output using your personal style, brand voice, or past writings.
6. Data Analysis and Research
- 1
Working with CSV, JSON, and Tables
Reliably process tabular data with Claude: cleaning, transforming, validating, generating control code, and verifying the result.
- 2
Statistical Interpretation and Visualization
Stories, not just numbers — interpret statistical results with Claude, with significance thresholds and visualization choices.
- 3
Long Document Summarization and Synthesis
From 200-page reports to a 1-page brief: map-reduce, anchored summarization, and faithfulness evaluation.
- 4
Comparative Analysis and Multi-Source Evaluation
Way to weigh conflicting sources together: source-reliability tagging, contradiction maps, synthesis bias checks.
- 5
Catching Hallucination and Verifying Sources
You can't eliminate hallucination but you can catch it. Systematize verification of Claude output with 6 techniques.
7. Claude's Superpowers
- 1
Tool Use: Granting Claude Real Capabilities
How to teach Claude to use a calculator, database, email, Slack, code sandbox? Anatomy of tool use and production patterns.
- 2
Vision: Image Understanding and Analysis
Screenshots, photos, charts, handwritten notes — extracting information from images with Claude vision, plus its limits.
- 3
PDF and Document Processing
Sending PDFs to Claude, extracting data from multi-page documents, and forms / contracts analysis.
- 4
Computer Use: Screen and Browser Control
Two capabilities where Claude controls your screen, browser, mouse and keyboard: Computer Use and Claude in Chrome. Includes safe-use practices.
- 5
Extended Thinking: Deep Reasoning Mode
Open the model's hidden thinking buffer on complex tasks: what extended thinking is, when to enable, and the cost.
- 6
Artifacts: Live Working Outputs
Mechanics of Artifacts — Claude's code, SVG, or React component live-rendered in a side panel. Build and iterate live.
8. Programmatic Claude with the API
- 1
Getting Started with the API: Auth, First Request, SDK Setup
Grab your API key from Anthropic console, install the SDK, run your first call. Python and TypeScript step by step.
- 2
Messages API: Multi-Turn Conversations
Building blocks of Messages API, system message, multi-turn conversation, response object, and token counting.
- 3
Streaming Responses and Real-Time UX
What streaming is, why it matters, and integration with SSE / Web Streams.
- 4
Tool Use API: Function Calling in Practice
Finish tool use over the API: full loop, parallel tools, error feedback, and schema validation.
- 5
Cut Cost up to 90% with Prompt Caching
Cache stable system prompts, large few-shot blocks, and long documents to slash input cost.
- 6
Batch API: Bulk Async Workloads
Run async workloads at 50% cost with the Batch API. Ideal for labeling, content generation, and evals.
- 7
Error Handling, Rate Limits, and Retry Strategies
Classify API errors, apply the right retry strategy, use idempotency keys, design DLQs.
9. Production
- 1
Eval Sets and LLM-as-Judge
Design eval sets that measure production quality: building, balancing, auto-scoring (LLM-as-judge), human calibration.
- 2
Prompt Injection, Jailbreak, and Defense
How adversarial users, malicious content, or manipulated data affect Claude — and eight defense patterns.
- 3
Cost Monitoring, Quotas, and Budget Alarms
Avoid bill surprises with a cost pipeline: per-user quotas, alarm thresholds, anomaly detection.
- 4
Latency, Caching, and Performance Optimization
Eight levers to reduce p50/p95/p99: model choice, caching, streaming, parallelism.
- 5
Logging, Tracing, and Observability
OpenTelemetry-compatible LLM tracing, structured log schema, error reporting, prompt-versioned observability.
10. Agent Design
- 1
What Is an Agent? Reactive vs Autonomous
Agent vs pipeline, the four building blocks (planner, memory, tools, controller), and which problems require an agent.
- 2
Build Your First Agent with the Claude Agent SDK
Hello-World agent with the Claude Agent SDK: tool definitions, system prompt, controller loop, and human approval.
- 3
Multi-Tool Agent Architectures (Planner-Executor)
Planner + executor separation, tool selection guidance, sub-agent invocation.
- 4
Memory, State, and Long-Term Context
Memory layers in multi-step / multi-session agents: scratch, episodic, semantic, user profile.
- 5
Human-in-the-Loop and Approval Flows
Gating risky agent actions through human approval: pre-execution diff, severity tier, audit log.
11. Real-World Projects
- 1
Project: Multilingual Customer Support Assistant
TR/EN support pipeline: intent, FAQ, escalation, CSAT feedback. Which step on which model, and how to design evals.
- 2
Project: RAG Document Q&A System
RAG over company docs: chunking, embedding, retrieval, re-ranking, anchored answers.
- 3
Project: Code Review Automation
PR review automation with GitHub Actions + Claude: diff parsing, rubric-based comments, severity labels.
- 4
Project: Content Production Pipeline
From topic list to publish: outline → draft → editor → SEO → image suggestion → CMS publish. Human approval at each step.
- 5
Project: Structured Data Extraction from PDFs
Invoices, contracts, forms — structured extraction with Claude vision + tool use. Accuracy metrics and audit trail.
12. Ecosystem and Certificate
- 1
MCP (Model Context Protocol) Integration
What is MCP and why? How to connect local/remote MCP servers to Claude. Examples with Slack, Notion, Postgres.
- 2
Skills, Plugins, and Marketplace
What are Skills, when to write one, what plugins are, how the marketplace works. Examples and publishing your own.
- 3
Community, Documentation, and Continuous Learning
Anthropic docs, cookbooks, Discord, papers, and a daily routine for keeping up.
- 4
Capstone Project + Final Quiz + Certificate
Real-world synthesis: design, build, and run an agent end-to-end, then take the final certification exam.
Frequently Asked Questions
- Modules are designed to be followed in the order shown in the table of contents. The first module lays the groundwork, later ones build on it. You can skip a section, but if a 'Prerequisites' block appears in a side module, complete those lessons first.