Deep Learning Course

Key Information on Upcoming Course Event

  • Full time, 3 Week, Live Instruction Course
  • July 08, 2024 – July 26, 2024
  • Applications are closed for the 2024 course.

Deep Learning Course

Learn Advanced Techniques and Apply Them Ethically to Advance Science

Code-First, Hands-On Learning

  • Our DL course emphasizes a hands-on, code-first approach with Python tutorials and teaching assistant support
  • You’ll gain practical experience through engaging in group projects that explore a variety of deep-learning techniques

Cutting-Edge Modeling Techniques

  • Our advanced curriculum features cutting-edge modeling techniques in deep learning.
  • You’ll learn core topics in DL, including linear DL, optimization, regularization, NLP, generative models, unsupervised learning, and reinforcement learning.

Ethical Considerations and Scientific Inquiry

  • Our DL course emphasizes ethical considerations and a scientific inquiry-based approach to deep learning
  • You’ll learn how to use DL to advance science and achieve better scientific insights

Suitable for All Backgrounds and Fields

  • Our DL course is perfect for anyone interested in learning and applying deep learning techniques, regardless of their scientific background or field of study.
  • You’ll have ample opportunities for practical experience through group projects with teaching assistant support.

Comprehensive Curriculum

  • Our DL course covers a wide range of topics and provides a comprehensive curriculum for mastering deep-learning techniques.
  • You’ll start with an introduction to DL models and their workings, followed by modules on machine learning, natural language processing, computer vision, and more.

Don’t miss out on this opportunity to dive deep into the world of Deep Learning with the guidance of our expert instructors and teaching assistants! Whether you’re a seasoned data scientist or just starting out, our DL course provides a comprehensive curriculum that covers all the core topics you need to know to become a proficient deep learning practitioner.

To see more, including the group projects, view the course schedule and course content here: Deep Learning Course


It is our priority to provide affordable, quality education in computational sciences to anyone anywhere in the world, but we must also make sure that our teaching assistants receive fair compensation for their work.

While we are supported by generous donations from a variety of foundations and industry partners, we strive to make our live courses sustainable by charging a small, regionally-adjusted tuition fee. This fee is (1) substantially lower than those of traditional summer schools, (2) determined by the location, career position, and funding status of each student individually, and (3) essentially in its entirety used to pay our teaching assistants.

See fee calculator here.

We do not want tuition fees to be a barrier for anybody, so fee waivers are available to students that need them without any impact on their admission. However, if you can pay even a part of your fee without hardship, we kindly ask that you do so. There is also an opportunity to pay more than your fee if you would like to help subsidize fee waivers for students with less financial means than yourself.


Our live course runs annually in July. We are considering the addition of a second live course in December/January, but a decision for next year has not been made yet.

Information for Teaching Assistants

Teaching assistants lead each student classroom and group research project team. They have ensure students collaboratively learn while also being available as a more experienced expert to answer questions and provide guidance to the pod.

Teaching assistants are paid, full-time, temporary, contracted roles. TA compensation is provided by this calculator.

You can read more about the TA role on our Courses Page or in the Portal.


Applications generally open three to four months before the course date. To check registration status and submit an application, visit our Portal, make a profile, and then apply for our course if it is available.