Free course · Advanced Technology
Machine Learning Starter
A free introduction to machine learning: the main types of learning, the end-to-end workflow, a few key algorithms, evaluating models and the realities of data quality and deployment.
Free · self-study · no certificate
About 6 hours
2 modules · 5 lessons
What you will be able to do
- Distinguish supervised and unsupervised learning
- Describe the machine learning workflow from data to evaluation
- Explain overfitting and how a model is evaluated fairly
Who it's for
- Learners with some Python who want to explore machine learning
- Analysts curious about predictive models
Before you start
Basic Python is helpful for the code examples.
Module 1 · about 120 minutes
Machine Learning Basics
Types of learning, the workflow and key algorithms.
- Describe the types of learning
- Follow a complete workflow in scikit-learn
Module 2 · about 80 minutes
Trustworthy Models
Evaluation, overfitting, data quality and deployment.
- Evaluate a model on unseen data
- Spot data-quality and ethics problems
Further learning
- scikit-learn — Getting Started — The official introduction to estimators, pipelines, model evaluation and parameter search in the open-source library used in this program.
- Machine Learning Crash Course (Google) — Google's practical introduction with videos, visualisations and exercises on regression, classification, data and fairness.
Continue with a full program
- Machine Learning (ML) — Build models that learn from data for prediction, classification, and decision-making.
- Data Science — Collect, clean, and analyze data to support decisions in government, NGOs, and business.
- Python — Practical Python programming for automation, data work and back-end development — from first scripts to a deployed, tested application.
Want the full Machine Learning (ML) program?
This free course is an introduction. The full program is taught live by an instructor, with practical assignments, assessments, projects and a certificate.
See the Machine Learning (ML) program