Summer 2018 Deep Learning Short Course

June 18th – June 22nd

Florida Atlantic University, Boca Raton, FL

What is Deep Learning?

Deep Learning is a type of Artificial Intelligence where we give the computer the ability to learn, rather than tell it what to learn. Here at MPCR, we look at Deep Learning as a member of multiple fields, if not every field. AI has its roots in Psychology and Biology, and we strive to remain true to those origins when we consider Deep Learning as a Theory of the Brain. However, it is also highly computational and is an important tool for today’s Data Scientists. Deep Learning has already begun to answer questions in fields such as Medicine, Biology, Chemistry, and Engineering, and it is gaining momentum. Understanding and contributing to the Deep Learning Movement in AI will have an impact both on the researcher, as well as society on the whole.


What can Deep Learning do?


We are putting these artificial brains to work in diagnosing cancer, finding potential new drugs to treat HIV, learning how to smell, and driving autonomously. These projects come from different fields, but converge on their approach: Deep Learning. MPCR is equipped with multiple Graphics Processing Units (GPUs) to run various types of Artificial Neural Networks (ANNs) on our data. With these resources, we firmly believe that Deep Learning will revolutionize many fields of science and engineering, allowing for new ways of analyzing data and generating new questions and methodologies. In this short course, we strive to provide participants with the skills to bring Deep Learning to their unique and diverse problems from any field.


What will be covered in this Short Course?

The goal of this course is to take someone with minimal or no prior experience in Deep Learning and give them both the conceptual framework to understand the algorithms, as well as the computational practice to be able to begin to deploy them in their home research settings.

Participants will gain hands-on experience of topics using Python via Colaboratory on Google Drive. They will also be introduced to some of the applied research projects currently taking place in the lab to see how Deep Learning can be applied to a wide range of problems. Students do not need any previous experience with Python or computer programming but will need to bring their own laptop computers to access the scripts online.

We will be covering four major topics:

  • Convolutional Neural Networks (CNNs)
  • Reinforcement Learning and Q- Learning
  • Generative Adversarial Networks (GANs)
  • Unsupervised Learning (e.g. PCA, k-means clustering, sparse coding)

The day-to-day schedule will consist of 10am to 4pm of content, with conceptual talks in the mornings and hands-on practice in the afternoons. Social events will be planned for the evenings, such as a BBQ on the beach.


Who should apply?

This short course is open to students that are interested in machine learning, and particularly deep learning. Faculty that are interested in attending are also welcome, but please email for the registration process. Students in high school, undergraduate, or graduate school are welcome to apply. Registration cost is $250 to cover meals and incidentals. A limited number of competitive scholarships are available by application. Students must bring their own laptop computers with WiFi capabilities.

  • There are no pre-requisite courses or skills for this short course. Students should be able to follow along with the Python scripts during the hands-on portion of the course without prior Python knowledge, as the code will be explained. However, some background in any programming language may be helpful.
  • Participants must be enrolled in school, either high school, undergraduate, or graduate
    • If you are a faculty member of a university and interested, please contact us directly as there is a different registration process, but space is available
  • Participants need to be able to attend the entire short course. If students are also enrolled in summer courses at FAU, that will be taken into consideration during the application process.

What is Included?

Registration fee goes towards covering lunches on Tuesday, Wednesday, Thursday, and Friday; dinners on Tuesday and Wednesday; and course materials.

Application Process

The application deadline is May 7th, 2018 May 18th, 2018. There is a basic application, with supplemental materials if applying for a scholarship. Participants will be notified of decisions by May 14th, if application is submitted on or before May 7th, otherwise it will be rolling admission and payment must be made by June 1st. The application consists of:

  • Demographic Information
  • Personal Statement (200 words max)
    • Your Personal Statement should focus on where your research interests lie, what research experiences you’ve had in the past, your motivation to learn about Deep Learning, how you would want to apply Deep Learning in your current and future research, etc.
  • Past Experience with Machine Learning/Deep Learning
    • This will not affect your likelihood of acceptance, but will be used after the registration process in order to have a sense of what knowledge students will have coming into the course
  • Travel information
  • Supplemental Application for Scholarship Consideration
    • 1 Letter of Recommendation from a faculty member
      • Letters should emphasize the commitment of the student, the student’s willingness to learn new skills, and the student’s overall motivation in and out of the classroom
      • Letters should be submitted to by May 18th, 2018
    • Student’s CV

There are a limited number of spots for students. Scholarships will be awarded based on merit, but will take into consideration other expenses such as travel and lodging.

 Apply Here!