AOS-7 Enterprise AI Platforms & Integration
AOS-7 Enterprise AI Platforms & Integration
- Course description
- Course CodeAOS-7
- Level of Study5.2
- Program of StudyAI Operations Specialist
- Credits12.5
- Study Plan CoordinatorMonde Sineke
This course focuses on integrating AI services with business systems and workflows. Students learn about enterprise integration, including APIs, messaging and event-driven communication. They develop and test integrations using existing AI services, simple agentic workflows and retrieval of organisational data, while considering security, reliability and business needs.
Students also learn to configure and manage services within existing enterprise AI platforms, including access to AI models, permissions, data connections, usage and costs. They explore information security, data protection, AI governance and relevant regulations, including traceability and accountability. Throughout the course, students document and explain their technical decisions and learn how to maintain integrations and AI platform services as technologies and organisational needs change.
The candidate...
- has knowledge of enterprise integration principles and architectures, including APIs, event-driven integration, messaging, managed AI services and retrieval-based AI solutions
- can assess integrations and AI platforms in relation to requirements for security, data protection, AI governance and regulation
- can update their knowledge of AI platforms, managed AI services and integration practices as they change
The candidate...
- can explain the design of an enterprise AI integration, including the choice of architecture, services and governance approach, to technical and non-technical audiences
- can assess integrations through testing, identify errors and determine what measures need to be implemented
The candidate...
- can plan and carry out the integration of AI services and agents with business systems and workflows, in accordance with ethical requirements and principles for responsible AI
- can contribute to organisational development by managing the usage, cost and resource allocation of AI platforms
Students use a combination of written content, videos and practical learning activities designed to help them achieve the course learning outcomes.
Industry Relevance
Course content, learning activities and tools reflect industry standards and are developed in collaboration with industry partners and experts from the field.
Practical Work
The course includes regular practical activities where students apply their knowledge and practise relevant skills.
Collaboration
Collaboration is facilitated through the LMS and Teams, and students are encouraged to work together for peer support and shared learning.
Guidance
Teachers are available for guidance at scheduled times. Students are encouraged to share work in progress and use feedback from teachers and fellow students to develop their work further.
| Form of assessment | Grading scale | Grouping | Duration of assessment |
|---|---|---|---|
Course Assignment | Pass / Fail | Individual | 2 Week(s) |