Artificial Intelligence
Machine Learning Essentials
Learn the core ideas behind machine learning: training data, features, labels, supervised and unsupervised learning, model evaluation and avoiding common mistakes such as overfitting.
Instructor: Future Ai LMS Faculty · English · intermediate
What you'll learn
- Explain supervised and unsupervised learning
- Prepare features and labels
- Evaluate models with the right metrics
- Recognise overfitting and bias
Who it's for
Learners who know the basics of AI and want to understand how models are built.
Prerequisites
AI Foundations for Everyone or equivalent. Basic spreadsheet or Python skills help.
Curriculum
3 modules · 5 lessons
Module 1: How Machines Learn
- Data, Features and LabelsPreview15 min
- Supervised vs Unsupervised Learning15 min
Module 2: Building Reliable Models
- Training, Testing and Evaluation15 min
- Overfitting, Bias and Responsible ML15 min
Module 3: Final assessment
- Final course quiz15 min