Courses
NMA 2023 Dates and Info
Course Begins - July 10, 2023
Course Ends - July 28, 2023
Applications for students and TAs are now closed.
Overview
Our summer courses are intensive 3-week programs (7+ hours/day) involving hands-on tutorials developed and taught by leading experts. Students are placed into TA-led groups of 10-20 students using the neuromatch algorithm, which matches students based on common interests, timezone, and their preferred language. They receive personalized support as they work through hands-on tutorials and collaborate on course projects.
In order to capture all aspects of traditional summer schools, students will also be offered to be mentored by professors in the field, professional development seminars, career panels, and opportunities to virtually socialize with their fellow students.
All of our course materials are freely available to use in your own courses, teaching experiences, and other content as all of our materials have a CC-BY license.
Please note that due to legal and liability restrictions, we are unable to accommodate students or teaching assistants who are under the age of 18.
Check the Roles page for more info about students, teaching assistants, and mentors.
Available Courses
We offer two courses: Computational Neuroscience and Deep Learning.
In addition to a brand-new 2 weeks virtual summer school within the Climatematch Academy.
Computational Neuroscience
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 projects with guided experience in modeling any observed phenomenon
Professional networking opportunities with TAs 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 project-specific TAs and expert mentor
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
Deep Learning
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
Pricing
Traditional summer schools can be expensive (~$5,000 for a three-week course), but Neuromatch promises to be always affordable while still ensuring our teaching assistants get paid. To do this, we charge a much lower, regionally adjusted fee, and fee waivers for students that need them without any impact on their admission.
While Neuromatch is supported by generous donations from a variety of foundations and industry partners, we strive to make the program sustainable through tuition fees, which are used to pay our teaching assistants. We do not want fees to be a barrier for anybody, so these fees can be waived, but if you can pay even part of your fee, this is welcome. There are even opportunities to pay more than your fee if you would like to help subsidize fee waivers for other students with less financial means than yourself.
To estimate your course fees based on your region, use our COLA Calculator.
ClimateMatch
Climatematch Academy (CMA) is a wide-reaching and brand-new summer school. It's an inclusive and approachable program aimed to introduce computational methods for climate science. The existing climate science research community severely underrepresents the global population that will be impacted by climate change. CMA strives to create a globally diverse climate sciences community, trained in cutting-edge techniques to access and analyze open-source modeled and observational climate data.
CMA offers a two-week program involving hands-on tutorials developed and taught by leading experts following the successful Neuromatch Academy format. Students will also be offered mentoring from experts, professional development seminars, career panels, and opportunities to virtually socialize with their fellow students.
To see more, including the group projects, view the course schedule and course content here: Climatematch Academy