Learn AI from fundamentals to real-world applications — Python, Machine Learning, Generative AI, LLMs, RAG, automation and an introduction to AI agents.
⏱Duration: 40 hours
💻Format: Instructor-Led + Labs
🌐Delivery: Classroom · Virtual · Hybrid
✅Pass rate: 94%
📅Next intake: 3 Nov 2026
🧠
AI foundations
ML, Deep Learning, Gen AI and agents
🐍
Python practice
Data, models and a working AI app
📚
RAG and LLMs
Ground answers in your documents
🛡️
Responsible AI
Privacy, security and human oversight
What this programme is
Learn AI from fundamentals to applications.
Artificial Intelligence is changing how businesses analyse data, create content, automate work, develop applications and make decisions. This practical, instructor-led programme takes you from AI fundamentals and Python into Machine Learning, Deep Learning concepts, Generative AI, Large Language Models, RAG, automation and an introduction to AI agents.
No prior AI or Machine Learning experience is required. You learn through instructor demonstrations, guided labs and practical projects.
This is broader than ChatGPT and prompting. Modern AI work needs data, Machine Learning, Generative AI, Large Language Models and intelligent applications working together. HRD Corp claim support is available for eligible employers.
Artificial Intelligence Training in Malaysia
A structured journey from AI fundamentals to applications you can demonstrate.
✓ Artificial Intelligence fundamentals and Python for AI
✓ Data preparation, Machine Learning, regression and classification
✓ Unsupervised learning and Deep Learning fundamentals
✓ Natural Language Processing, Generative AI and Large Language Models
✓ AI applications, RAG, automation and an introduction to AI agents
✓ Responsible AI, privacy and security
Hands-On AI Projects
This is not a theory-only AI course. You build a portfolio during the programme.
✓ Python data analysis and Machine Learning model development
✓ Regression, classification and customer segmentation
✓ Neural-network fundamentals and NLP
✓ Generative AI, LLM applications and RAG
✓ AI automation, an introduction to AI agents, and a final capstone
Technologies and tools
You gain exposure to tools commonly used in modern AI development. Platforms may be updated as the technology changes.
✓ Python, Jupyter Notebook, NumPy, Pandas and Matplotlib
✓ scikit-learn and PyTorch or TensorFlow
✓ Large Language Models, LLM APIs, embeddings and vector databases
✓ RAG and Git / GitHub
AI Course Certification
On successful completion you receive the Nexperts Academy Professional Certificate in Artificial Intelligence.
The certificate recognises instructor-led training and practical coursework in Artificial Intelligence.
AI Learning Path
After this programme you can continue into the area that matches your goal.
AI and Machine Learning
✓ Predictive models, Machine Learning, Deep Learning and further model development.
AI-powered software development
✓ Using modern AI development tools to build software and applications.
Agentic AI Engineering
✓ Applications that use tools, knowledge, context and multi-step workflows.
Traditional AI can analyse, predict and generate. Agentic systems can also retrieve information, use tools and run multi-step workflows. Continue with Agentic AI Engineering.
Who should take this course
🌱
Beginners
Start Artificial Intelligence with no prior ML experience.
💼
Professionals
Upskill for AI work in your current role.
💻
Developers
Add Machine Learning, LLMs and AI apps to your stack.
📊
Analysts
Move from reports into models and intelligent apps.
🎓
Graduates
A structured path into practical AI.
🚀
Founders
Understand AI products, RAG and automation.
Prerequisites
✓ Basic computer literacy
✓ No previous AI or Machine Learning experience required
✓ Programming is helpful but not mandatory — essential Python is taught in class
→ Ask enrolment for a free readiness checklist before class.
Curriculum
Fifteen modules. From foundations to a capstone.
The syllabus moves from AI fundamentals and Python through Machine Learning, Deep Learning, NLP, Generative AI, RAG, automation, agents and a final project.
Hands-on Labs
Practice. Reviewed.
You leave with a portfolio: data work, models, an LLM application, a RAG assistant and a capstone demonstration.
01
Python data
Load, clean and analyse a real dataset.
Data
02
ML models
Regression, classification and clustering.
ML
03
Gen AI
LLM app, RAG assistant and a simple agent workflow.
AI
04
Capstone
End-to-end AI solution you can present.
Project
+ Mentor office hours for sticky blockers.
Assessment
Practical checkpoint. Certificate.
Complete the guided labs and the final capstone to earn the Nexperts Academy Professional Certificate in Artificial Intelligence.
Completion rubric
LabsCore labs completed with tutor sign-off
ProjectMini-project meets the published checklist
AttendanceMinimum attendance threshold met
PassingCertificate issued
ResitOne remediation session included
Our 3-Mock Exam Programme
01
Concept check
Quick quiz after each module.
02
Lab review
Peer + tutor feedback.
03
Project dry-run
Present before final submit.
0%
Pass Rate
94% complete labs on schedule.
We keep cohorts small enough for real feedback — not slide-only delivery.
AI foundationsPython practiceRAG and LLMs94% passMentors
Why our pass rate is 94%
Self-paced video only
No reviewed artefact.
Nexperts
Lab sign-off + mentor feedback.
Your next step
Keep building the pathway.
Stack related AI and data programmes once foundations are solid.
