Machine learning is a field of artificial intelligence (AI) that allows computers to learn from experience and improve their performance on tasks without being explicitly programmed to perform these tasks, e.g., predicting future house prices from historical data and trends. The rapid growth of data from sources such as the web and social media as well as fields such as healthcare and finance has made machine learning increasingly important in AI and a central competency in computer science.

This course will introduce basic machine learning concepts, covering data preparation, supervised and unsupervised techniques, evaluation, as well as specific approaches such as neural networks. You will learn to formulate a machine learning task from a range of real-world data from a variety of domains, apply machine learning techniques using open-source machine learning frameworks, and evaluate their effectiveness.