Virtual Training
Research, Data Analytics, and Business Intelligence
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.
5 Days
Duration
Live Online
Delivery
12 Dates
Available
Certificate
Included
Master advanced machine learning to build high-performance predictive models, automate MLOps workflows, and deliver explainable AI insights using industry-standard frameworks and tools.
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
1
Advanced Feature Engineering and Data Preprocessing
2
High-Performance Ensemble Learning and Boosting
3
Deep Learning Architectures for Predictive Modelling
4
Automated Hyperparameter Tuning and Optimization
5
Explainable AI and Model Interpretability
6
MLOps and the Machine Learning Lifecycle
7
Ethical Governance and Strategic Integration
Built for Papua New Guinea
From your market
Real tools and case studies from Papua New Guinea — taught against the configurations and outcomes you'll actually encounter.
Industry Tools and Platforms Featured in this Training
5-
Scikit-learn scikit-learn developersUsed for classical machine learning workflows such as preprocessing, model selection, and validation in Python-based analytics projects.
-
XGBoost XGBoost ContributorsUsed for high-performing gradient-boosted tree models on structured business data, especially when accuracy and tuning matter.
-
TensorFlow GoogleUsed for building and deploying neural-network models when teams need scalable deep learning workflows.
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MLflow LF AI & Data FoundationUsed to track experiments, manage model versions, and support repeatable machine-learning deployment pipelines.
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Apache Spark Apache Software FoundationUsed to process large datasets and support distributed feature engineering and model training at scale.
Where this course runs
Advanced Machine Learning and Predictive Modelling Training is delivered in the cities below — pick the one that fits your schedule.
