Design, build, and deliver production-grade AI solutions using Anthropic’s Claude platform.
This advanced training prepares technical professionals for the Claude Certified Architect – Professional certification by developing practical skills in AI solution architecture, model selection, prompt and context management, system integration, RAG, evaluation, optimization, security, and governance. Participants learn to translate business needs into reliable Claude-powered solutions and support them throughout the development lifecycle.
- Why get trained: Learn to design complete Claude-based AI systems, integrate tools and data sources, build retrieval-based solutions, evaluate performance, and apply security and governance controls.
- Why it matters: Build production-ready AI solutions that balance accuracy, performance, cost, reliability, security, and business requirements.
- Who should attend: Solution Architects, AI/ML Engineers, Technical Leads, Senior Software Engineers, AI Solution Designers, Claude Production Professionals, AI System Design & Implementation Professionals, and AI Security, Governance & Technical Decision-Making Professionals.
Participants gain practical experience through real-world scenarios, hands-on workshops, and expert guidance aligned with professional-level certification objectives. HRD Corp Claimable.
Overview
The Claude Certified Architect – Professional certification validates your ability to design, build, and deliver production-grade AI solutions using Anthropic’s Claude platform.
The certification assesses your ability to turn business needs into practical AI solutions, choose the right models and approaches, work with Claude in existing systems, improve system performance, and consider security, compliance, and governance when designing solutions.
This is an independent certification exam, not a mandatory training program. There are no mandatory prerequisites or courses required to take the exam.
Skills Covered
- Turn business problems into practical Claude-based AI solutions
- Design complete AI systems from input to output and ongoing improvement
- Choose the right approach for workflows, agents, and other AI solutions
- Select Claude models based on the needs of a specific use case
- Create effective prompts and manage the information given to Claude
- Connect Claude with tools, APIs, data sources, and existing systems
- Design retrieval-based solutions for working with business data
- Test AI solutions and improve their accuracy, speed, cost, and reliability
- Apply security, safety, compliance, and risk controls
- Communicate technical decisions clearly with stakeholders
- Support AI solutions throughout design, implementation, deployment, and ongoing improvement
- Use Claude tools to improve developer workflows and resolve operational issues
Prerequisites
The certification is designed for mid- to senior-level technical professionals who have experience designing and delivering AI solutions. It is not intended for entry-level developers or people without experience designing complete AI systems.
Target Audience
- Solution architects
- AI/ML engineers
- Technical leads
- Senior software engineers
- Professionals designing AI-powered solutions
- Technical professionals working with Claude in production
- Professionals responsible for AI system design and implementation
- Professionals involved in AI security, governance, or technical decision-making
The certification is designed for mid- to senior-level technical professionals who have experience designing and delivering AI solutions. The recommended profile includes 3+ years of experience in systems architecture or platform engineering, at least 6 months of hands-on experience with Claude or similar AI systems in production, and experience taking systems from discovery through deployment. This experience is recommended, not a mandatory eligibility requirement.
Module 1: Solution Design & Architecture
Learn how to turn business needs into practical Claude-based solutions. This includes designing complete systems, choosing between different approaches, working with multiple agents, breaking down complex problems, and connecting technical decisions to business goal.
Module 2: Claude Models, Prompting & Context Engineering
Understand how to choose the right Claude model for different needs, create clear system instructions, improve prompts, manage the amount of information given to Claude, and reuse prompts effectively.
Module 3: Integration
Explore how Claude can work with existing tools, systems, and data. Topics include access and security requirements, balancing speed and accuracy, monitoring systems, working with business data, retrieval-based solutions, and choosing the right way to connect different systems.
Module 4: Evaluation, Testing & Optimization
Learn how to check whether an AI solution is working well. This includes measuring accuracy, speed, cost, and safety, creating test data, comparing different approaches, finding problems such as incorrect responses or unsuitable models, and improving overall performance.
Module 5: Governance, Safety & Risk Management
Understand how to make AI solutions safer and more responsible. This includes setting safety controls, identifying risks and limitations, deciding when human review is needed, meeting regulatory requirements, and considering fairness and transparency.
Module 6: Stakeholder Communication & Lifecycle Management
Learn how to understand stakeholder needs, explain technical decisions clearly, manage expectations, document solutions, and support an AI system throughout its lifecycle from initial planning to ongoing improvement.
Module 7: Developer Productivity & Operational Enablement
Explore how Claude tools such as Claude Code can support development teams. This includes improving everyday development work, helping with debugging, and resolving operational issues.
Exam & Certification
Training & Certification Guide
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