Data Science: Machine Learning
Data Science: Machine Learning
Title: Data Science: Machine Learning
Author for citation: Rafael Irizarry
License for content: Unknown
Publication date: 2024
This is a Harvard University-created course that is released on the edX platform. The introductory eight-week course will have you "learn popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system." The course is free to take. A verified certificate of completion, as part of Harvard's Data Science Professional Certificate Program, is available afterwards for $149 USD. The session started on January 2, 2024 and ends on June 19. Enrollment for the free Audit track ends February 27. An additional session begins on April 17.
The edX course description:
"Perhaps the most popular data science methodologies come from machine learning. What distinguishes machine learning from other computer guided decision processes is that it builds prediction algorithms using data. Some of the most popular products that use machine learning include the handwriting readers implemented by the postal service, speech recognition, movie recommendation systems, and spam detectors.
In this course,part of our Professional Certificate Program in Data Science, you will learn popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system.
You will learn about training data, and how to use a set of data to discover potentially predictive relationships. As you build the movie recommendation system, you will learn how to train algorithms using training data so you can predict the outcome for future datasets. You will also learn about overtraining and techniques to avoid it such as cross-validation. All of these skills are fundamental to machine learning."
"What you'll learn:
- The basics of machine learning
- How to perform cross-validation to avoid overtraining
- Several popular machine learning algorithms
- How to build a recommendation system
- What is regularization and why it is useful?
About the authors
The course is taught by Rafael Irizarry, Professor of Biostatistics at Harvard University. "For the past 15 years, Dr. Irizarry’s research has focused on the analysis of genomics data. During this time, he has also has taught several classes, all related to applied statistics. Dr. Irizarry is one of the founders of the Bioconductor Project, an open source and open development software project for the analysis of genomic data."
General layout and contents of the course
No formal syllabus is provided on the course welcome page.
The course
: The course can be found on the edX site, under the Data Analysis category. The session started on January 2, 2024 and ends on June 19. Enrollment for the free Audit track ends February 27. An additional session begins on April 17.
