What is Machine Learning?
Machine learning uses algorithms to learn patterns from data and make predictions or decisions. This beginner course introduces the workflow, vocabulary, and core model types.
Where is Machine Learning used?
- Classification and prediction
- Recommendation and ranking
- Forecasting and anomaly detection
- Language, image, and signal applications
Prerequisites to learn Machine Learning
- Basic Python
- High-school algebra and introductory statistics
- Curiosity about data and experimentation
Advantages of Machine Learning
- Can discover useful patterns at scale
- Automates decisions that are hard to specify as rules
- Applies across many domains
- Improves through measured iteration
Limitations of Machine Learning
- Results depend heavily on data quality
- Models can reproduce bias
- Training and evaluation require careful design
Start learning Machine Learning
Open the course contents menu to follow the lessons in order, or choose the topic that matches your current goal.
