Claude Certified Associate - Foundations
Use Claude safely and effectively for business, research, analysis, and productivity workflows.
Operations, project, sales, marketing, finance, support, research, and other knowledge-work professionals. No software-development experience is required.
60
Questions
120 min
Time limit
$99
Exam fee
720 / 1000
Passing score
Multiple-choice and multiple-response
Format
Proctored online or at a test center
Delivery
12 months
Validity
v1.0 · July 2026
Guide
Exam domains
Weighted objectives straight from the exam guide.
Prompting and Task Execution
14%- Create effective prompts for business and technical tasks
- Decompose complex requests into manageable work
- Iterate prompts using observed output quality
- Adapt prompting to analysis, research, drafting, and brainstorming
Output Evaluation and Validation
21%- Evaluate accuracy, completeness, and audience fit
- Identify hallucinations, inconsistencies, and bias
- Fact-check against authoritative evidence
- Choose when human review or additional verification is required
- Refine and compare outputs
- Select appropriate inline, artifact, and structured formats
Product and Model Selection
12%- Choose among Projects, research, chat, and artifacts
- Differentiate Haiku, Sonnet, and Opus roles
- Balance quality, speed, and cost
- Manage context and memory by restarting, summarizing, or persisting
Workflow Integration and Solution Design
16%- Analyze requirements and candidate use cases
- Apply Claude to research, planning, and process improvement
- Support solution design and iteration
- Augment or redesign existing workflows
- Communicate value and limitations to stakeholders
Configuration and Knowledge Management
12%- Configure Projects with instructions and knowledge
- Manage uploads and connectors
- Write effective persistent instructions
- Maintain configurations and sources over time
Governance, Risk, and Responsible Use
15%- Separate appropriate from inappropriate use cases
- Apply privacy, data-sensitivity, and regulatory constraints
- Follow organizational AI policy
- Recognize ethical implications and escalate risk
Troubleshooting and Optimization
10%- Diagnose underperforming prompts and poor outputs
- Adjust the approach using feedback and results
- Optimize workflows for efficiency and effectiveness
Study path · 9 lessons
Go deeper in the main curriculum
Prompt Engineering
Build prompt structure and iteration from first principles
Context Engineering
Understand context limits and deliberate context assembly
LLM Evaluation
Turn quality judgment into repeatable tests
Guardrails
Layer responsible-use controls around model behavior
Bias and Representational Harm
Recognize and evaluate harmful output patterns