BMI 707 - Deep Learning for Biomedical Data (2 credit course, offered in spring)

Faculty: Andrew Beam, Nils Gehlenborg, Kun-Hsing Yu

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Deep learning is a type of machine learning methods that employed many layers of data representations to capture the characteristics of the input data at different levels. It is inspired by the organization of neurons in organisms and has shown superior performance in image classification, natural language processing, and predicting of gene functions. In this class, we will introduce the basic concepts of deep neural networks and GPU computing, discuss convolutional neural networks and recurrent neural networks structures, and examine a few biomedical applications. Students are expected to be familiar with linear algebra and machine learning and will participate in a group deep learning project.

Course available to all Harvard and MIT students with permission. Please reach out to Rebecca Fitzhugh ( for details.

Spring 2 Semester 2018 

Meeting Times: Wednesday 2PM-5PM
Location: Countway, Room 403 (all classes)
Meeting Dates: 

  • Week 8- March 21                                   
  • Week 9- March 28          
  • Week 10- April 4                                    
  • Week 11- April 11                                    
  • Week 12- April 18                                  
  • Week 13- April 25                                    
  • Week 14- May 2