Part-time
8–10 committed hours / week
16 weeks. Plan for guided instruction, enterprise case work, reading, practice, and assessment activities alongside your existing commitments.
The AI Solutions Engineer Mastery programme is an advanced online course for experienced engineers and architects who want to move beyond prototyping and lead AI delivery at enterprise scale. Choose part-time delivery over 16 weeks or full-time delivery over 8 weeks.
Five advanced areas that take you from prototyping to production-grade delivery.
| Competency | What you'll learn |
|---|---|
| Advanced AI Architecture | Designing scalable, resilient AI systems with microservices, event-driven patterns, and multi-model orchestration |
| Multi-Agent Systems | Building governed multi-agent pods with role assignment, inter-agent communication, and human-in-the-loop checkpoints |
| Enterprise Deployment | CI/CD, monitoring, observability, blue-green deployments, and production operations for AI systems |
| Governance and Compliance | PDPA, GDPR, ISO 42001, AI risk frameworks, audit logging, and responsible AI deployment |
| AIRPF Framework Application | Applying the AI Risk and Prompt Framework to real enterprise scenarios for responsible governance |
This programme is designed for experienced professionals ready to lead AI delivery.
| Audience | Background |
|---|---|
| Senior Engineers | 5+ years of software engineering, ready to lead AI system architecture |
| Solution Architects | Experienced in system design, expanding into AI-native architectures |
| Tech Leads | Managing development teams, needing AI delivery governance expertise |
| AI Practitioners | Working with AI tools, seeking structured enterprise-grade methodology |
Five intensive modules designed for experienced professionals. Both schedules follow the same curriculum and enterprise-focused outcomes.
| Module | Focus | Outcome |
|---|---|---|
| 1. Advanced Architecture | Scalable AI system design, microservices, event-driven patterns, multi-model orchestration | Design production-grade AI architectures that scale |
| 2. Multi-Agent Systems | Governed multi-agent pods, role assignment, inter-agent communication, human-in-the-loop | Build and orchestrate multi-agent systems with governance |
| 3. Enterprise Deployment | CI/CD for AI, monitoring, observability, blue-green deploys, production operations | Deploy and operate AI systems with enterprise confidence |
| 4. Governance & Compliance | PDPA, GDPR, ISO 42001, AI risk frameworks, audit logging, responsible AI | Navigate regulatory requirements and implement AI governance |
| 5. Enterprise Case Study | End-to-end enterprise AI project: scoping, architecture, delivery, governance, handover | Lead a full AI delivery cycle at enterprise scale |
Fully online. Choose part-time delivery over 16 weeks or full-time delivery over 8 weeks, with enterprise-scale projects and team exercises.
Both formats cover the same learning outcomes, projects, and assessment standard. Full-time delivery compresses the same work into a shorter calendar period and requires protected study time.
16 weeks. Plan for guided instruction, enterprise case work, reading, practice, and assessment activities alongside your existing commitments.
8 weeks. The accelerated schedule suits learners who can protect larger blocks of time each week for architecture, delivery, governance, and case-study work.
| Requirement | Minimum / recommended setup |
|---|---|
| Computer | 64-bit PC or Mac with a modern multi-core CPU, 16 GB RAM recommended (32 GB is helpful for local containers or models), and at least 50 GB of free SSD space. |
| Operating system | A supported current Windows, macOS, or Linux host with permission to install development tools. Windows learners may use WSL2 where required by the course tooling. |
| Development tools | Python 3.11+, Git, a modern code editor, Docker Desktop or an equivalent container tool, and a current browser. Course tools may include OpenClaw, Ollama, n8n, FastAPI, Streamlit, and ChromaDB or Qdrant. |
| Internet and collaboration | Stable internet access of at least 20 Mbps, webcam and microphone for online sessions, and reliable access to the learning and collaboration platforms. |
| AI runtime | Instructor-approved local or cloud AI services may be used depending on the exercise. Local model execution is optional and can require additional memory, storage, or setup. |
| Access and safety | Ability to install or obtain support for the required tools, keep credentials private, and use synthetic or approved data in exercises rather than production secrets. |
You should have professional software engineering experience (5+ years recommended) and foundational AI knowledge. This programme moves fast and assumes you can write production code.
The programme is delivered fully online. It runs part-time over 16 weeks or full-time over 8 weeks, and the fee is SGD 3,000 nett.
Plan for about 8–10 committed hours per week part-time or 18–20 hours per week full-time. You need a 64-bit PC or Mac, 16 GB RAM recommended (32 GB is helpful for local containers or models), at least 50 GB of free SSD space, a current operating system, Python, Git, a code editor, Docker or an equivalent container tool, and reliable internet. Running local AI models may require additional memory and storage.
The Apprenticeship is an intermediate programme covering practical foundations over 24 weeks part-time or 12 weeks full-time. Mastery is an advanced programme over 16 weeks part-time or 8 weeks full-time, focused on enterprise architecture, multi-agent systems, governance, and production delivery. If you can already build a basic AI workflow, the Mastery programme is for you.
Yes. The final module is an enterprise case study where you'll scope, architect, build, deploy, and govern a full AI system — the same process we use for our client engagements.
We cover PDPA (Singapore), GDPR (EU), ISO 42001 (AI Management Systems), and the AIRPF (AI Risk and Prompt Framework). You'll learn to apply these frameworks to real AI deployment scenarios.
Book a call to discuss the mastery programme and whether it's right for you.