AI Engineering:
Permanent Upskilling for Technical Staff
Build production AI systems, from model orchestration to data pipelines. Master MCPs, RAG architecture, multi-model routing, and AI analytics. Designed for developers, data engineers, and technical leads.
Workshop Dates
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Dates Coming Soon
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Register Interest via WhatsAppPrivate Corporate Training
Looking to upskill your entire engineering or data team?
Exclusive sessions available for groups of 25-35 pax per class. Fully HRDC claimable.
What You'll Build
Hands-on projects you will architect and deploy during the course.
RAG-Powered Knowledge Base
Build a production RAG system with document ingestion, semantic search, and retrieval evaluation.
Multi-Model API Gateway
Route requests to optimal models based on task complexity, cost, and quality requirements.
Automated Data Pipeline
Design ETL pipelines that transform raw data into AI-ready feature stores and vector indexes.
AI-Powered Analytics Dashboard
Natural language querying over business data with automated insight generation.
Custom MCP Server
Build Model Context Protocol servers that connect AI systems to external tools and data sources.
Document Processing System
Automated extraction, classification, and summarization of business documents.
AI Monitoring Dashboard
Real-time monitoring of model performance, cost tracking, and drift detection.
HRDC Training Architecture
A structured, hands-on approach to mastering AI engineering for production systems.
Day 1: AI Engineering Foundations & Model Theory
Understanding the paradigm shift and building your first production AI endpoints.
Core Theory
- AI Engineering Paradigm: AI Engineering vs Traditional Software — the fundamental paradigm shift in how we build software.
- Model Landscape & Selection: Understanding GPT, Claude, Gemini, Llama, Mistral — architecture, context windows, tokenization, and choosing the right model.
- Evaluation & Cost Engineering: Model evaluation frameworks (benchmarks, MMLU, human eval), token pricing, caching strategies, model tiering, cost-per-task analysis.
- Prompt Engineering for Developers: System prompts, chain-of-thought, structured outputs, tool use patterns.
Working Examples Built in Class
Configure Claude API, OpenAI, and local model endpoints for development.
Build a production-ready API with structured output parsing and validation.
Same task across 3 models — evaluate quality, speed, and cost trade-offs.
Connect language models to SQL databases for dynamic natural language querying.
Day 2: MCPs, Multi-Model Orchestration & Data Pipelines
Connecting AI to the real world with production-grade architecture patterns.
Core Theory
- Model Context Protocol (MCP): Architecture, servers, tool registration, and integration patterns for connecting AI to the real world.
- Multi-Model Orchestration: Routing, fallbacks, evaluation loops, and ensemble patterns for production systems.
- RAG Architecture: Document ingestion, chunking strategies, embedding models, vector databases, and retrieval evaluation.
- Data Pipeline Design: ETL for AI systems, feature stores, vector indexing, and data quality management.
Working Examples Built in Class
Create and deploy a Model Context Protocol server with tool registration.
Full RAG pipeline with semantic search and retrieval quality evaluation.
Build a system that selects the optimal model per task based on complexity and cost.
Automated data processing pipeline combining n8n orchestration with AI agents.
Day 3: Analytics Architecture & Production Systems
Phase 03Deep dive into analytics architecture, production deployment, and enterprise AI platform design:
- AI analytics architecture: from raw data to intelligent insights
- Building AI-powered dashboards with NL-to-SQL
- Data warehouse design patterns for AI workloads
- Real-time vs batch analytics trade-offs
- Production monitoring: drift detection, quality scoring, cost tracking
- Security, governance, and compliance
- Designing scalable enterprise AI platform architecture
- Corporate AI strategy and technical roadmap
Who Should Attend?
This intensive is designed for technical professionals who want to build production-grade AI systems.
Software Engineers & Developers
Engineers building AI-powered applications and integrating LLMs into existing systems.
Data Engineers & Data Scientists
Professionals designing data pipelines, analytics systems, and ML infrastructure.
Technical Leads & Engineering Managers
Leaders responsible for AI engineering strategy, architecture decisions, and team upskilling.
DevOps & Platform Engineers
Teams deploying, monitoring, and scaling AI systems in production environments.
Experience the Workshop
Join a growing community of AI engineering professionals across Malaysia.
Our People
Learn from Malaysia's top AI engineering practitioners.
Dr Poo Kuan Hoong
Data Science, ML & AI Specialist
Deep expertise in AI/ML and Data Science platforms. Specialist in production-ready analytics solutions — spanning modern data engineering, MLOps, predictive workflows, and enterprise AI architecture. Advisor to national AI initiatives.
Tze Jin
AI & ML Specialist
Deep expertise in machine learning and backend logic. Guides participants on integrating complex AI reasoning, database structures, model deployment, and building production-grade AI engineering systems.
Detailed FAQ
Addressing your technical, logistical, and HRDC inquiries.
Course Fee
Transparent pricing for your AI engineering transformation.
Self-Funded (non-HRDC)
Kickstart your AI Engineering journey
- 3 full days of intensive training
- Complete course materials & templates
- Certificate of Completion
- 3-month post-training support
- Private community access
HRDC-Claimable
Upskill with your company's HRDC grant
- 3 full days of intensive training
- Complete course materials & templates
- Certificate of Completion
- 3-month post-training support
- Private community access
About AITraining2U
AITraining2U was established by professionals to close the divide between academic theory, business and practical industry demands. Our mission is to ensure that AI education translates directly into measurable, real-world results. Since 2025, we have upskilled over 1,200 professionals across Malaysia in AI, Business Transformation, Agentic Automation, and Vibe Coding.
Driven by a core philosophy of "100%-focus on success" our expert faculty delivers highly interactive, hands-on learning experiences focused entirely on implementation. We don't just teach prompt engineering; we teach you how to architect robust, autonomous systems.
Whether through bespoke corporate masterclasses or intensive public bootcamps, we actively partner with enterprise leaders, technical specialists, and government bodies to accelerate their digital transformation journey and build confident, AI-native organizations.