Artificial Intelligence & Machine Learning Course Malaysia
Build practical Machine Learning models with Python — data preparation, regression, classification, clustering, evaluation and neural networks in 40 hours.
⏱Duration: 5 days / 40 hrs
💻Format: Instructor-Led + Labs
🌐Delivery: Classroom · Virtual · Hybrid
✅Pass rate: 94%
📅Next intake: 17 Nov 2026
📊
Real models
Regression, classification and clustering
🐍
Python ML
NumPy, Pandas and scikit-learn
🎯
Evaluation
Choose metrics that match the problem
🧠
Neural nets
A first Deep Learning model
What this programme is
Build practical Machine Learning models.
Learn how machines learn from data and build practical Machine Learning solutions using Python. The programme covers fundamentals, data preparation, supervised learning, regression, classification, unsupervised learning, clustering, model evaluation and neural networks.
The workflow is: understand the problem, prepare the data, select a model, train, evaluate, improve and predict. You work with real datasets throughout the five days.
This programme goes deeper on Machine Learning than a general AI survey: data, algorithms, training, prediction, classification, clustering and evaluation. Generative AI is introduced for context. HRD Corp claim support is available for eligible employers.
Learning outcomes
After 40 hours you should be able to take a dataset through a complete Machine Learning project.
✓ Explain AI and Machine Learning concepts
✓ Prepare data and run exploratory analysis
✓ Build regression, classification and clustering models
✓ Choose metrics and address overfitting
✓ Understand neural networks and build a basic model in Python
Hands-on projects
✓ Data preparation and exploratory data analysis
✓ Regression and numerical prediction
✓ Classification and model comparison
✓ Customer segmentation with clustering
✓ A basic neural network
✓ End-to-end Machine Learning capstone
Technologies and tools
✓ Python and Jupyter Notebook
✓ NumPy, Pandas and Matplotlib
✓ scikit-learn
✓ TensorFlow / Keras or PyTorch
✓ Git / GitHub
Tools may be updated to match current industry practice.
Certification
Participants who complete the programme requirements receive the Nexperts Academy Professional Certificate in Artificial Intelligence and Machine Learning.
Continue your AI learning journey
Advanced Machine Learning and Deep Learning
✓ Neural networks, computer vision, NLP and further model work.
AI Engineering and Agentic AI
✓ LLM applications, RAG, tools, APIs, workflows and agents.
✓ Programming is helpful but not mandatory — required Python is taught in class
✓ Basic maths and statistics help; advanced mathematics is not required
→ Ask enrolment for a free readiness checklist before class.
Curriculum
Five days. A complete ML workflow.
Day 1 builds AI, Python and data foundations. Days 2 to 4 cover regression, classification, model improvement and clustering. Day 5 introduces neural networks and the capstone.
Hands-on Labs
Practice. Reviewed.
Five guided projects plus a final capstone, from raw data to a trained and evaluated model.
01
Prepare data
Clean and explore a real dataset with Python.
EDA
02
Regression
Predict a numerical outcome and score it.
Predict
03
Classification
Compare algorithms and pick a winner.
Classify
04
Clustering
Segment customers with K-Means.
Cluster
05
Neural net
Train a basic neural-network model.
DL
06
Capstone
Raw data to a trained, evaluated model.
Project
+ Mentor office hours for sticky blockers.
Assessment
Practical checkpoint. Certificate.
Complete the labs and the end-to-end capstone to earn the Nexperts Academy Professional Certificate in Artificial Intelligence and Machine Learning.
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.
Real modelsPython MLEvaluation94% 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.