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.

Computational Neuroscience Course

Learn Computational Neuroscience in a Hands-On Way

Pre-Course Preparation

• Optional 12-video series covering essential neuroscience topics, Python, and mathematics

Code-First, Hands-On Learning

• Learn cutting-edge advances in machine learning and causality research with state-of-the-art modeling approaches in neuroscience.
• Focus on interpretability and the process of modeling.
• Group research projects with guided experience in modeling any observed phenomenon
• Professional networking opportunities with instructors and expert mentors

Course Curriculum

• Introduction to modeling, types of questions we can ask with given model types and creating your own models.
• Machine learning module: fitting models to data, using generalized linear models, uncovering underlying lower dimensional structures, and building complex models using deep learning
• Dynamical system module: building biologically plausible models based on bottom-up knowledge of the system being modeled, covering topics like linear systems and dynamic networks
• Stochastic processes module: methods for getting better insight through measurement tools, hidden dynamics, optimal control, and reinforcement learning
• Causality module: understanding when something is causally related vs. just correlated

Get Ready to Launch into Your Neuroscience Journey

• Full-time effort of 8 hours per day, 5 days per week
• Code taught through Google Colab or Kaggle using Python
• Work in a pod of ~15 students and a teaching assistant
• Supported by research project guides

Don’t miss your chance to explore the intersection of neuroscience and machine learning. Our computational neuroscience course is the perfect way to gain practical experience and build a strong foundation in this field. Join us and become part of a growing community of scientists and researchers exploring the frontiers of computational neuroscience.

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

Pricing

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.

Dates

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.

Apply

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.