Machine learning is a core technology of artificial intelligence and data science that enables computers to act without being explicitly programmed. Recent advances in machine learning have given us, inter alia, self-driving cars, AlphaGo, Amazon, and Netflix. This technology has also allowed us to predict armed conflict and post-electoral violence, detect fake news, develop targeted provision of care and public services, and implement early policy interventions. This course provides a hands-on introduction to machine learning. By the end of this course students will have a sound understanding of the key concepts of machine learning, the ability to analyse data using some of its main methods, and a solid foundation for more advanced or more specialised study. The course covers topics in supervised and unsupervised learning, including the most common learning algorithms for regression, classification and clustering, such as random forests, neural networks, and dimensionality reduction techniques. Students will learn the fundamental concepts underlying machine learning algorithms, and we will equally focus on the practical use of machine learning algorithms using open-source frameworks.
This course is for 1st year MDS students only.
Instructor
- Slava Jankin , Fellow
