Applied Machine Learning
Implementing the classical algorithms that power modern intelligence.
Modules7 Sessions
Duration11 weeks
Outcomes5 Skills
Course Overview
This is where the predictive power of AI becomes tangible. You will implement and tune the core algorithms that define the field: from linear regressions that predict house prices to sophisticated k-means clustering that segment customer behaviours. We move beyond theory to true application, focusing on model evaluation, hyperparameter tuning, and the critical 'bias-variance tradeoff' that every machine learning engineer must master.
Tools & Technologies
Scikit-LearnXGBoostK-MeansModel Evaluation Kits
Curriculum
7 ModulesWhat You'll Learn
- Implement supervised learning models for regression and classification
- Deploy unsupervised clustering algorithms for pattern discovery
- Execute rigorous model evaluation using cross-validation
- Tune hyperparameters to optimise model performance
- Navigate the mathematical foundations of gradient descent
Prerequisites
- Data Science & Analytics