COURSES · AI & AUTOMATION · MALAYSIA
Mastering AI Advantage for Next-Gen Productivity and Impact.
Next-gen productivity and impact for an AI-native economy.
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Course overview.
AI PRODUCTIVITY TRAINING MALAYSIAMove from casual AI prompting to practical problem-solving at work. This course connects an understanding of language models with the communication, context and critical-thinking skills needed to use them effectively.
Learn to write clear prompts, supply useful context, check AI outputs and recognise hallucinations, bias and over-agreeable responses. Explore how to verify and disclose AI-assisted work before colleagues rely on it.
Apply those foundations to writing, research, visual communication, presentations, video and software prototypes. Hands-on labs progress from focused exercises to a multimodal launch project: a strategic brief, announcement, visual assets, short explainer and working prototype.
The emphasis is on practical judgement and reusable working methods. Participants build and refine useful outputs, evaluate the tools they use and learn where human review remains essential.
Key takeaways.
AI PRODUCTIVITY TRAINING MALAYSIA- Establish a "Chain of Trust" to ensure accountability and eliminate the reputational risks of sharing unverified AI outputs
- Secure sensitive data by correctly selecting between Public, Enterprise and Sovereign environments based on requirements
- Correct the "sycophancy trap"—where AI lies to be agreeable—to prevent expensive strategic errors driven by blind trust in the model.
- Move beyond trial-and-error prompting to command AI with precision using the RCTF+C framework, eliminating ambiguity and rework
- Transform mediocre "first draft" AI outputs into professional deliverables using advanced logic audits and iteration protocols
- Decompose complex business problems into atomic steps for reliable AI execution, ensuring human judgment remains in the loop
- Replace manual searching with Agentic Research workflows that synthesize data into cited, decision-ready briefs in minutes.
- Translate text strategies into persuasive visual assets and broadcast-quality video—without needing external agencies
Who should attend.
This course is designed for modern professionals and business leaders who need to move beyond unstructured experimentation with AI to driving tangible business impact. Highly recommended for:
- C-Suite Executives: CEOs, CTOs, CIOs, CFOs and leaders defining AI governance, safety standards, and workforce ROI
- Directors & Functional Heads
- Team Managers & Supervisors
- Strategy & L&D Leaders
- Product & Project Managers
- Business Owners
- Anyone who wants to transition from casual prompters to AI-native problem solvers
Prerequisites.
No prior knowledge of programming, AI or LLM is required.
The programme.
AI PRODUCTIVITY TRAINING MALAYSIASESSION 1AI Competence & "chain Of Trust" In The Workplace
- Outcome: Explain why AI competence is a professional standard
- Core Skills for 2030 (World Economic Forum Framework):
- AI & Big Data, Tech Literacy, Analytical/Creative Thinking
- The New Risk: "The Chain of Trust":
- Reality: We rely on work by colleagues using AI.
- Risk: Colleague's AI hallucinations become your strategy
- Standard: Verify before sharing, disclose AI use
- Lab: Draft 3-point protocol (disclosure, verification, judgment)
SESSION 2The Two Brains Of AI — Traditional Vs. Generative
- Outcome: Choose the right AI setup for data sensitivity
- Traditional AI: Deterministic & Logical
- Traceability: "White Box" — You can audit the decision
- Generative AI: Probabilistic & Adaptive
- Traceability: "Black Box" — Hard to trace reasoning
- The LLM Landscape (The 3 AI Environments Trade-off):
- Public cloud: Maximum Intelligence vs. Minimum Privacy
- Enterprise tenant: Integration vs. Restricted Capability
- Private stack: Total Control vs. High Effort
- Privacy basics: what never goes into public tools, how enterprise controls work, why "shadow AI" happens
SESSION 3How Large Language Models (llms) Think
- Outcome: Explain hallucinations and spot "agreeable" bias
- Transformers and attention: Why context works
- LLMs training: Learns statistical relationships, not truths
- Think of an LLM as autocomplete on steroids
- Prediction vs. Thought: LLMs do not "know" the answer; they calculate the probability of the next word (token)
- Hallucinations: When the model lacks data, it fills the gap with statistically probable words to stay fluent
- The "Agreeableness" Trap (RLHF & Sycophancy)
- The Yes-Man: Model interprets "Helpful" as "Validating"
- Sycophancy: AI will prioritize aligning with your view over providing objective truth, reinforcing your biases
- Lab: Sycophancy test and grounding drill
SESSION 4Prompt Engineering Fundamentals – Communication Mastery
- Outcome: Write clear prompts using RCTF + constraints
- Prompt: Communication between human + AI
- "New Intern" mental model: AI as a brilliant but literal intern
- The R.C.T.F. + C Framework:
- Role: Who is the AI?
- Context: The Background
- Task: The Directive
- Format: The Output
- Zero-shot vs few-shot examples
- Why prompting still matters: AI can read context, but it can't read your mind
- Lab: Rewrite a generic prompt by applying R.C.T.F. + 3 Examples (Few-Shot)
SESSION 5Advanced Prompt Techniques
- Outcome: Use reusable prompts and structured reasoning
- From sentences to structured commands
- Variables and placeholders
- Chain-of-Thought (CoT) Prompting
- Meta-prompts: Using AI to write your prompts
- The core skills behind good prompting
- Communication skills: clarity, tone, context
- Critical thinking: goal definition, reasoning steps
- Information design: structure, format and output framing
- Lab: Solve a trade-off using a step-by-step CoT prompt chain
SESSION 6Context Is Everything — Grounding AI In Your Work
- Outcome: Provide input that improves accuracy and relevance
- "Garbage In, Garbage Out" - Context quality
- Context Injection theory: Training data vs context
- Delimiters and structured inputs (tables, bullets)
- Managing limitations: Token limits and "Lost in the Middle"
- Lab: "Context Injection" Drill - Raw paste vs structured context
SESSION 7Evaluating And Improving AI Outputs - Escaping The "average"
- Outcome: Critique outputs and drive better iterations
- "Regression to the mean" problem: AI is trained to maximize probability - towards the "safest," most average answer
- Recency bias: Obsess over the last instruction
- Techniques to extract excellence:
- Force-rank options
- Use comparison tables to visualise trade-offs
- Confidence check: State confidence score
- Advanced Iteration Protocols:
- The Critique (Logic Check)
- Head on the Block/Skin in the Game (Liability Check)
- AI Tribunal (LLM vs. LLM): Model-to-model critique, creating a true "Red Team" effect
- Lab: The "Average to Excellence" Sprint - Apply advanced iteration protocols to transform the draft into a high-stakes deliverable
SESSION 8Critical Thinking And Problem Decomposition
- Outcome: Break big work into atomic steps and audit results
- Fluency illusion: Good grammar does not equal good logic
- 3 cognitive blind spots:
- Automation bias
- Confirmation bias
- "Negative Space" flaw
- "Zero-trust" review of AI outputs in team workflows
- "Cognitive supply chain" theory: AI cannot solve "big" problems but excels at atomic tasks (specific, singular)
- The "human sandwich" framework
- Techniques for decomposition: dependency mapping, "pseudo-code" discipline
- Lab: The Logic Blueprint (decomposition drill): Build a 4–5 step prompt chain, compare output of a chain vs a mega-prompt
Theme: "stop Chatting, Start Building."
- Applying Day 1's foundational skills to produce finished, professional-grade assets — decks, briefs, videos, and prototypes — using AI as your execution layer.
SESSION 9Writing That Doesn't Sound Like AI – Killing "AI Slop"
- Application: Emails, proposals, reports that protect credibility
- Detect slop: inflated importance, empty verbs, filler metaphors, connector addiction, safety wrapper
- Fix with constraints: banned words, no intro/outro padding, contractions, varied rhythm
- Style transfer using 3 writing samples, then run the "ear test"
- Lab: "Signature Voice" Sprint - Draft a memo or post, iterate until it passes as human
SESSION 10Research To Decision — From Questions To Strategic Clarity
- Application: Turn research into a decision-ready brief fast
- Shift: Google keyword search > multi-step agentic research commands
- Triangulation: Multi-model verification. Research with one model, critique with another
- Synthesis matrix: Comparison table, gaps, recommendation
- Source audit: Credibility, recency, corroboration, confidence
- For deep research with citation: Perplexity Pro, HuggingChat
- For document analysis: Google NotebookLM, Claude
- For Visual Research Synthesis: Genspark
- For Agentic Browsing (Search > Action): Atlas, Comet
- Lab: The Deep Research Sprint - A fully cited, one-page strategic brief/executive summary
SESSION 11Visual Communication — Translating Ideas Into Imagery
- Application: Communicate visually with deck, one-pager, diagram
- Visual fluency gap: Fix by converting language into visual descriptions AI can render
- Visual communication techniques:
- Style anchor lock visual consistency
- Narrative deck: hook> problem > solution > proof > CTA
- The visual asset workflow:
- Photos & imagery: Gemini Nano Banana Pro (paid), Midjourney (paid), Microsoft Bing Image Creator (free)
- Vectors & icons: Recraft.ai (freemium)
- Diagrams & logic: Napkin.ai (free beta)
- The Presentation & Layout:
- For presentations: Gamma (freemium), Canva (free tier), Microsoft Copilot PPT/Plus AI (for Google Slides)
- For documents & one-pagers: Canva Magic Design, Microsoft Designer
- Lab: Visual Sprint - Transform text brief into 3 visual assets in 45 minutes
- Generate assets: images/process diagram
- Build one-pager with Canva
- Diagrams & build deck with Gamma
SESSION 12Multimedia Communication — Video Without A Production Team
- Application: Create professional videos using language prompts
- AI has collapsed the production barrier
- "Uncanny Valley" problem: Fix with 3-second rule, audio > video, motion = interest
- Video production techniques:
- Script-for-ear: short sentences, pauses, simple phrasing
- Direct motion: zoom, pan, focus shifts, b-roll coverage
- Audio-first workflow: voiceover, then visuals, assembly
- Video Production Workflow
- Voice: ElevenLabs (freemium), HeyGen
- Face (Avatars): HeyGen (freemium), D-ID (free trial)
- Footage (B-Roll): Google Veo 3 (paid), Runway Gen-3 Alpha (limited), Luma Dream Machine (free Tier)
- Assembly: CapCut, Canva Video, DaVinci Resolve
- Lab: Storyboard 3 shots, generate clips, assemble and export
SESSION 13Rapid Prototyping — From Concept To Clickable "product Thinking"
- Application: Turn ideas into demos for stakeholder buy-in
- "Builder Mindset" Shift
- Write a mini-PRD: users, actions, data fields, success criteria
- Iterative build: structure > logic > polish
- Produce an artefact developers can take over
- For UI/Frontend Prototypes: v0.dev (Vercel), Claude Artifacts
- For Full-Stack Applications: Bolt.new, Lovable. Replit Agent
- Lab: Functional Prototype Sprint - Build a budget tracker (add items, table, totals, export)
SESSION 14Capstone: The "multimodal Launch"
- Application: Move from "vague idea" to "full execution"
- The Challenge: "The 24-Hour Launch"
- Situation: You have been tasked with launching a new internal initiative
- The Protocol: Choose stacks that best tell your story
- Research: 1-page Strategic Brief (cited)
- Content: Announcement email that passes "Robot Detector"
- Visual: 5-slide Deck or One-Pager
- Video: 15-30 second explainer
- App: Live sign-up page or dashboard
- Final Demo: Present your "Launch Package" to the group — the initiative, the assets, and one technique that made the biggest difference.
Your trainer.
AI PRODUCTIVITY TRAINING MALAYSIAAlvin Yong
MSc, FCCA(UK)
Alvin Yong is a UK-registered Fellow Chartered and Certified Accountant (FCCA). He obtained his Master of Science in Professional Accountancy (Merit) in 2017 from the University of London.
To bring.
AI PRODUCTIVITY TRAINING MALAYSIASoftwareMicrosoft Copilot — Laptop with Internet Browser
Reviews from our Malaysian clients.
AI PRODUCTIVITY TRAINING MALAYSIA“Content is very good, notes are sufficiently detailed, presentation is clear and pace is good. Alvin entertained questions calmly, clearly, and with sufficient depth. Very knowledgeable and qualified for the training subject.”
Manager, Strategy & Planning, Petronas
“Alvin is an excellent trainer. He led interesting, interactive and focused discussions during the workshop.”
Business Development & Partnership Manager, eBay
“Alvin was well prepared, knowledgeable and easy to follow. Level of detail was where it needed to be and the documentation was very thorough. The course went quickly which was always a good sign.”
VP of Finance - APAC, Middle East & Africa, FIS Global
“Fantastic trainer in terms of knowledge and skills. Extremely friendly, helpful and patient.”
Manager, Global Credit Policy and Portfolio Risk, Standard Chartered Bank
“Good understanding and knowledge of the subject. Attentive and responsive to participants' queries. Presented the subject very clearly.”
Learning & Development Specialist, Micron Semiconductor
“The trainer is knowledgeable. He was helpful. He handled the class material well.”
Financial Planning & Controlling Manager, Arvato Bertelsmann
“Very informative. Gave an excellent count of how-to's.”
Regional Component Planner, Komatsu Australia
“Alvin is a very people person. Sound knowledge in his area of expertise. He carried out the programme well.”
CEO, Felda Prodata Systems
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