Study guide
30 lessons across 7 domains
Each lesson maps to one exam objective. Mark lessons complete as you go; your progress is saved in this browser.
1 Prompting & Task Execution
14% of exam- 1.1Create effective prompts for business tasks7 min
- 1.2Apply task decomposition techniques6 min
- 1.3Iterate prompts to improve output quality5 min
- 1.4Adapt prompting strategy to the task type6 min
2 Output Evaluation & Validation
21% of exam- 2.1Evaluate output for accuracy and completeness6 min
- 2.2Identify hallucinations, inconsistencies and bias7 min
- 2.3Fact-check and validate outputs6 min
- 2.4Decide when human review is required5 min
- 2.5Edit and adapt outputs for the intended audience5 min
- 2.6Choose the right output format4 min
3 Product & Model Selection
12% of exam- 3.1Select the right Claude feature for the task7 min
- 3.2Differentiate Haiku, Sonnet and Opus4 min
- 3.3Align model choice with cost, speed and quality4 min
- 3.4Manage context limits and memory6 min
4 Workflow Integration & Solution Design
16% of exam- 4.1Analyse requirements and use cases6 min
- 4.2Use Claude for research, planning and process optimisation5 min
- 4.3Support solution design and iteration5 min
- 4.4Integrate Claude into existing workflows6 min
- 4.5Communicate Claude's value and limitations5 min
5 Configuration & Knowledge Management
12% of exam- 5.1Configure Claude Projects5 min
- 5.2Manage uploaded knowledge and connectors6 min
- 5.3Write effective system-level instructions6 min
- 5.4Keep configurations current over time4 min
6 Governance, Risk & Responsible Use
15% of exam- 6.1Identify appropriate and inappropriate use cases6 min
- 6.2Apply data-sensitivity, regulatory and privacy rules8 min
- 6.3Follow organisational AI governance policy5 min
- 6.4Reason through the ethical implications of AI use6 min
7 Troubleshooting & Optimization
10% of exam- 7.1Diagnose and resolve underperforming prompts6 min
- 7.2Adjust your approach based on feedback and results4 min
- 7.3Optimise AI workflows for efficiency5 min