Advanced Machine Learning and Predictive Modelling Online Course
Join our virtual, live instructor-led session and master Advanced Machine Learning and Predictive Modelling Training from anywhere in the world.
Upcoming Virtual Training Schedules
Join from anywhere in the world with our live instructor-led sessions
| Code | Start Date | End Date | Duration | Fee | |
|---|---|---|---|---|---|
| AML-07 | Mon - Fri (5 Days) | USD 1,050 | Reserve my seat → Register my team → | ||
| AML-07 | Mon - Fri (5 Days) | USD 1,050 | Reserve my seat → Register my team → | ||
| AML-07 | Mon - Fri (5 Days) | USD 1,050 | Reserve my seat → Register my team → | ||
| AML-07 | Mon - Fri (5 Days) | USD 1,050 | Reserve my seat → Register my team → | ||
| AML-07 | Mon - Fri (5 Days) | USD 1,050 | Reserve my seat → Register my team → | ||
| AML-07 | Mon - Fri (5 Days) | USD 1,050 | Reserve my seat → Register my team → |
Here's What You'll Learn
Each module tackles real challenges you face in your role
Advanced Feature Engineering and Data Preprocessing
High-Performance Ensemble Learning and Boosting
Deep Learning Architectures for Predictive Modelling
Automated Hyperparameter Tuning and Optimization
Explainable AI and Model Interpretability
MLOps and the Machine Learning Lifecycle
Ethical Governance and Strategic Integration
Market-specific guidance for Malaysia
A country-aware view of the pressures, proof points, and practical tools that shape how this course applies locally.
Tools and platforms relevant to this field
6Field-relevant examples that may be featured in training where they support the confirmed scope. Exact coverage depends on participant needs and delivery format.
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Scikit-learn scikit-learn developersUsed to build and validate classical machine learning workflows such as preprocessing, feature selection, model comparison, and cross-validation.
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XGBoost Tianqi Chen and contributorsUsed for high-performing gradient-boosted tree models in tabular prediction tasks where accuracy and feature interactions matter.
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TensorFlow GoogleUsed to develop and deploy neural-network-based models for more complex predictive tasks.
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MLflow DatabricksUsed to track experiments, manage model versions, and support reproducible model deployment workflows.
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FastAPI TiangoloUsed to expose trained models as APIs for integration into business systems and production services.
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Docker Docker, Inc.Used to package model code and dependencies into portable containers for consistent deployment across environments.
Where this course runs
Advanced Machine Learning and Predictive Modelling Training is delivered in the cities below — pick the one that fits your schedule.
