About this course
Machine Learning is a growing field that is used when searching the web, placing ads, credit scoring, stock trading and for many other applications.
This data science course is an introduction to machine learning and algorithms. You will develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics. We will also examine why algorithms play an essential role in Big Data analysis.
This is the second course in the three-part Data Science and Analytics XSeries.
What you’ll learn
● What machine learning is and how it is related to statistics and data analysis
● How machine learning uses computer algorithms to search for patterns in data
● How to use data patterns to make decisions and predictions with real-world examples from healthcare involving genomics and preterm birth
● How to uncover hidden themes in large collections of documents using topic modeling
● How to prepare data, deal with missing data and create custom data analysis solutions for different industries
● Basic and frequently used algorithmic techniques including sorting, searching, greedy algorithms and dynamic programming
Meet the instructors
Professor of IEOR and of Computer Science
Professor of Computer Science and Statistics
Associate Professor of Computer Science
Professor of Computer Science
Assistant Professor of Statistics