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20 curriculum modules
Intermediate
Analyze, Build and Troubleshoot
Develop practical skills in data flow, APIs, webhooks, testing, debugging, Python foundations and system reliability.
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Learning objectives
What you will learn
- Trace data through connected automation systems.
- Understand JSON, HTTP APIs, webhooks and authentication.
- Design integration tests and investigate execution logs.
- Apply introductory Python, machine learning and database concepts.
- Improve workflow reliability, security and monitoring.
Full module breakdown
Explore all 20 modules
The following titles reflect the curriculum for this stage. Each module contributes to the practical skills developed throughout the programme.
- 01 Thinking Like an AI Problem-Solver
- 02 How Automation Systems Work
- 03 Data and Data Flow
- 04 JSON for AI Automation
- 05 APIs and HTTP Communication
- 06 Webhooks and Event-Driven Workflows
- 07 Integration Testing and Test Cases
- 08 Logs and Execution History
- 09 Debugging and Root-Cause Analysis
- 10 Authentication and Authorization
- 11 Data Mapping and Validation
- 12 Error Handling and Workflow Reliability
- 13 Python Foundations for AI Systems
- 14 Machine Learning Foundations
- 15 Large Language Models and Structured AI Outputs
- 16 Database Foundations and Data Persistence
- 17 AI System Monitoring and Observability
- 18 Security and Safe System Operation
- 19 Incident Response and Technical Documentation
- 20 Intermediate Capstone and Final Examination
Learning by doing
Practical assignments & assessment
- Build a multi-step workflow using structured data and integrations.
- Test an API or webhook connection with representative inputs.
- Investigate deliberately introduced workflow failures and document fixes.
- Complete the Intermediate Capstone and Final Examination.
Expected learning outcome
You will be able to analyze data flows, test integrations, troubleshoot automation failures and explain essential security and reliability controls.