For AI training for software developers and IT teams in Malaysia, Dr Muhamad Hariz Muhamad Adnan (drhariz.com), HRD Corp certified AI trainer and Senior Lecturer at UPSI, runs hands-on programmes on AI coding assistants, LLM APIs, retrieval-augmented generation (RAG) and secure use. Sessions are built around your own stack and company policy, delivered on-site or live online in English or Bahasa Melayu.
Most Malaysian software teams already use an AI coding assistant, often without a shared policy, a review standard or any training. The result is uneven: a few developers get large productivity gains, others paste sensitive code into public tools, and team leads cannot tell whether AI-written code is being reviewed properly. This guide sets out what a developer-focused AI programme should cover, how it differs from general staff AI training, and how IT managers in Malaysia usually organise and fund it.
Why developers need different AI training from other staff
General corporate AI workshops focus on writing emails, summarising reports and drafting presentations. That content is useful for office teams, but it does not help a backend engineer decide whether to trust a generated database migration, or a team lead set rules for AI-assisted pull requests. Generative AI, meaning models such as GPT, Gemini, Claude and Llama that produce text and code from a prompt, changes the daily work of developers in specific ways: how code is written, how it is reviewed, how applications are built on top of model APIs, and how company data is protected along the way.
A developer programme therefore starts from engineering tasks. Participants work in their own languages and frameworks, on realistic repositories, and the hands-on time is spent on the decisions developers make every day.
What a developer AI training programme should cover
Teams rarely need every module at once. Most IT managers pick two or three based on where the team is today. A broader view of course types by role is in Best AI Courses for Companies in Malaysia, and a full module list is in the AI training syllabus for Malaysian companies.
1. AI coding assistants in daily work
Effective use of assistants such as GitHub Copilot, Gemini Code Assist, Claude and ChatGPT inside the IDE: writing clear instructions, giving the model the right context, generating tests first, refactoring legacy code, explaining unfamiliar codebases and writing documentation. The emphasis is on when the assistant helps and when it slows a developer down.
2. Reviewing AI-generated code
AI-written code can look correct and still be wrong. This module covers review habits for AI-assisted pull requests: checking edge cases, verifying that suggested libraries and functions actually exist, spotting outdated APIs, and keeping test coverage meaningful. Team leads leave with a short review checklist they can add to their pull request template.
3. LLM API fundamentals
For teams building AI features into products: calling model APIs, structuring prompts in code, handling tokens, cost and latency, getting structured output such as JSON, and evaluating responses so that features can be tested like any other code. Participants build a small working feature during the session.
4. Retrieval-augmented generation (RAG)
Retrieval-augmented generation connects a language model to a company’s own documents so answers are grounded in internal knowledge rather than the model’s general training. The module covers chunking, embeddings, vector search and evaluation, with attention to Bahasa Melayu and mixed-language content, which many Malaysian organisations hold. Background reading: RAG for Bahasa Melayu.
5. Secure and responsible use
What must never be pasted into a public AI tool, how to treat secrets and credentials, risks such as prompt injection and insecure generated code, and how personal data obligations under Malaysia’s Personal Data Protection Act 2010 (PDPA) apply when customer data passes through AI systems. This module is often the one management asks for first.
6. Team policy and workflow
Turning the above into a written team standard: approved tools, data classification rules, review requirements for AI-assisted code, and how to measure whether AI use is actually improving delivery. The output is a draft policy the IT manager can adapt and circulate.
Who the programme is for
- Software developers and engineers (backend, frontend, mobile and full-stack).
- QA and test engineers who want to generate and maintain tests with AI.
- DevOps and infrastructure staff writing scripts and configuration.
- Data and analytics teams moving from notebooks to AI-enabled applications.
- Team leads, engineering managers and IT heads who set policy and review standards.
Mixed groups work well for the policy and security modules. The API and RAG modules suit participants who already write code regularly.
Formats that suit IT teams
Developer programmes are usually run in one of three ways:
- One-day intensive covering coding assistants, code review and secure use, suitable for a whole team.
- Two-day build workshop adding LLM APIs and RAG, where participants finish with a working prototype.
- Short live online sessions spread over several weeks, which suit teams that cannot pause delivery for full days or that work across several offices.
Each format is adapted to the team’s languages, cloud platform and internal rules on which AI tools are allowed.
HRD Corp claims for developer AI training
HRD Corp claimable means a registered employer can use its HRD Corp levy to fund the training, subject to the scheme and approval process. Technology companies, software houses and IT departments of registered employers can generally fund developer AI training this way when it is delivered by an HRD Corp certified trainer. Confirm the scheme and the grant application with your HR team before the training date.
About the trainer
Dr Muhamad Hariz Bin Muhamad Adnan holds a Doctorate in Artificial Intelligence and is a Senior Lecturer at the Faculty of Computing and Meta-Technology, Universiti Pendidikan Sultan Idris (UPSI). He is an HRD Corp certified AI trainer focused on AI-driven digital transformation in education and the workplace, and delivers training in Bahasa Melayu, English or bilingually. Details of corporate programmes are on the corporate AI training Malaysia page.
How to prepare your team
- List the AI tools developers already use, officially or not.
- Confirm which tools and data your IT and security policy allows.
- Pick two or three modules from the menu above based on current gaps.
- Prepare a sample repository or internal documents that can safely be used in class.
- Agree how you will measure results, for example review findings or cycle time.
Frequently asked questions
It usually covers AI coding assistants, reviewing AI-generated code, LLM API fundamentals, retrieval-augmented generation (RAG), secure and responsible use including PDPA considerations, and a written team policy for AI-assisted development.
Dr Muhamad Hariz Muhamad Adnan (drhariz.com) delivers developer and IT team programmes. He holds a Doctorate in Artificial Intelligence, is a Senior Lecturer at the Faculty of Computing and Meta-Technology, Universiti Pendidikan Sultan Idris (UPSI), and is an HRD Corp certified AI trainer.
Registered HRD Corp employers can generally use their levy for training delivered by an HRD Corp certified trainer. Check the applicable scheme and submit the grant application through your HR team before the training starts.
No for the coding assistant, security and policy modules, which suit mixed technical teams. The LLM API and RAG modules work best for participants who already write code regularly.
Yes. Sessions can be delivered on-site or live online, including short sessions over several weeks for teams that cannot stop delivery for full days.
Plan a developer AI programme
To arrange AI training for your software or IT team, contact Dr Hariz with your team size, main languages and tools, and preferred dates.
