Agentic AI & AI Agents Training Malaysia (2026) — HRDF Claimable
Agentic AI is the next step beyond chatbots — AI that can plan, use tools, and complete multi-step tasks on its own. Agentic AI training in Malaysia teaches teams to design, build, and deploy AI agents that automate real work: from customer support and data processing to end-to-end business workflows.
Quick Answer: Agentic AI & AI Agents Training
What is it: Training to design and deploy AI agents — autonomous, tool-using AI that completes multi-step tasks. Covers agent frameworks, workflow automation (n8n, MCP), and multi-agent orchestration.
Who is it for: Developers, automation and IT teams, product managers, and technically-minded business users who want to automate workflows with AI agents.
Typical cost: RM1,500–RM4,000 per participant for a 1–2 day course; deeper developer/build programmes cost more. HRDF claimable under SBL-Khas.
What You'll Learn
- Understand agentic AI vs chatbots — planning, tool use, and autonomy
- Build AI agents and automate workflows with n8n, Make and MCP
- Orchestrate multi-agent systems using Claude, GPT and open-source tools
- Connect agents to your data and apps (RAG, APIs, integrations)
- Deploy agents safely — guardrails, oversight, and governance
Who Should Attend
Developers, automation and IT teams, data and operations professionals, product managers, and technically-minded business users building AI-powered automation.
Full Curriculum: What This Training Covers
That's the outcome — here's exactly how we get you there, module by module. A typical programme is organised into these modules; content is tailored to your team, roles, and industry.
1.Foundations of Agentic AI & Autonomous Systems
Traces the shift from predictive and generative AI to agentic AI, covering how autonomous, goal-oriented agents differ from standard chatbots by planning, deciding, and acting with minimal human intervention.
2.Structuring Agent Goals, Actions & Context
Defines the building blocks of an agent's "blueprint" — purpose, instructions, knowledge sources, prompts, and boundaries — and how these inputs are structured using recognised agent frameworks to shape reliable behaviour.
3.Reasoning & Interaction Patterns for Autonomous Execution
Covers reasoning loops and interaction patterns (e.g. plan-act-reflect cycles) that guide how an agent interprets context and chooses actions to complete multi-step tasks autonomously.
4.Core Technical Mechanisms: MCP & RAG
Introduces Model Context Protocol (MCP) for connecting agents across platforms and tools, and Retrieval-Augmented Generation (RAG), including agentic RAG, for grounding agent outputs in accurate, trustworthy data.
5.Building Agents with Zero-Code & Low-Code Tools
Hands-on design and development of AI agents using no-code/low-code platforms such as Make.com, Langflow, and Google AI tools, alongside developer-oriented frameworks like Autogen and LangGraph, for participants across technical and non-technical backgrounds.
6.Orchestrating Multi-Agent Workflows & Business Integration
Covers coordinating multiple agents into end-to-end workflows and integrating them with everyday business applications and productivity tools (e.g. Microsoft Copilot, ChatGPT) for automation and information retrieval tasks.
7.Governance, Safety & Human-in-the-Loop Controls
Addresses risk assessment, bias, transparency, and accountability in deploying agentic AI, and how to design human-in-the-loop checkpoints and boundaries so autonomous agents remain safely overseen within an organisation.
8.Applied Practice & Workplace Use Cases
Guided practical exercises applying agentic AI to real workplace scenarios — directing agents with clear inputs and boundaries, evaluating outcomes, and assessing readiness for organisational rollout.
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Agentic AI & AI Agents Training Programmes Available
Frequently Asked Questions About Agentic AI & AI Agents Training
A chatbot answers prompts; an AI agent can plan a task, use tools (search, code, apps), take multiple steps, and act toward a goal with minimal supervision. Agentic AI training focuses on building these autonomous, tool-using systems rather than just writing prompts.
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Ringkasan dalam Bahasa Melayu
Latihan agentic AI di Malaysia mengajar pasukan membina ejen AI yang boleh merancang, menggunakan alat, dan menyelesaikan tugas berbilang langkah secara automatik — merangkumi rangka kerja ejen, automasi aliran kerja (n8n, MCP), dan orkestrasi berbilang ejen menggunakan Claude dan GPT. Terdapat trek untuk pengguna perniagaan dan pembangun. Boleh dituntut melalui HRDF (SBL-Khas).
Prefer to Learn Online at Your Own Pace?
If in-house or public-class Agentic AI & AI Agents Training isn't what you need right now, these self-paced online certificates are a self-funded alternative. Not HRDF claimable — for personal upskilling, not company-sponsored training.
Last Verified: July 2026