02-620 Machine Learning for Scientists
02-620 COURSE PROFILE
|Special Permission Required? (If yes, see “Notes:)||No|
|Course Relevance (who should take this course?)||Graduate students in computational biology and graduate students who are interested in machine learning methods for scientific data analysis.|
|Background Knowledge||Programming skill. Basic knowledge of linear algebra, probability, and statistics|
Coursework will consist of the following components. No late assignments will be accepted.
Homework assignments. (45% of grade) Written homework assignments will test your knowledge of the material covered in class.
Attendance and participation. (10% of grade) Attendance will be taken, and we will have occasional in-class exercises that serve to reinforce the concepts we have covered. These exercises will not be graded, but participation will be expected in order to receive a complete grade for that day. You are allowed three “dropped” attendance grades without penalty. These can be used for any purpose.
Examinations. (45% of grade) The exams will test your knowledge of the material from the class. The two midterms will be held in class, and the final exam will be held during the university’s scheduled time. The exam dates are:
The midterms will not be cumulative: midterm 2 will cover material encountered after midterm 1. The final exam will cover the material from the entire semester.
|Most Recent Syllabus||02-620 Syllabus Spring 2020|
|Course Goals/Objectives||Students who complete this course will be able to:
|Pre-reqs, Cross List, Related||
|Updated December 2019|