BeyondAI
Introduction to AI and Research
Join our free international twelve-week research programme for undergrads and eager high schoolers to get started in the world of AI and Machine Learning!
Applications are open!
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Interested in AI?
From the 8th of September to the 30th of November you will embark on an exciting journey through the world of Machine Learning. Learn the basics and engage with more advanced material on Machine Learning and AI. Get introduced to the world of academic research and tackle a research project with your team! From beginners to more advanced, we offer resources for everyone! Expand your knowledge and make your first steps into the world of AI research.
Whether it is classical Machine Learning or Deep Learning, we have you covered!
The programme at a glance
The twelve-week programme consists of two parts: the Course Stage and the Research Stage. In the Course Stage you'll be taught about the basic concepts of modern Machine Learning & AI via a problem-based approach. We'll combine both mathematical thinking with practical coding. You'll be also introduced to the world of research.
In the Research Stage you will be conducting a research project in a group under the guidance of an academic mentor. You'll finish with bang by presenting your research poster at our
BeyondAI Research Fair
and have it published in our proceedings!
Learning Time
By engaging in interactive live sessions in the first 6 weeks, we will get you covered in the basics of Machine Learning & AI conceptually, theoretically and practically. There will be also sessions to build your skillset as a researcher, as well as networking sessions with your peers and our alumni.
Mentor-guided Research
After you have been assigned a team and an academic mentor in the 6th week, you will apply your learning and skills while working on a group research project for 6 weeks! To keep expanding your horizon you will attend talks by academics and industry experts talking about their work and research in AI and ML.
Presentation
Your research is complete and your poster is ready. Now, take the spotlight at our BeyondAI Research Fair — a chance to showcase your work to the public, connect with experts, and network with leading companies. Have your research published in our official proceedings. Congratulations on completing the programme!
See the final projects of some of our students!
They are published in our programme research proceedings, go and check them out!
Application Requirements
- Be an undergraduate, or high school student (gap years are also considered)
- Be curious and passionate about the world of AI (we accept all levels of expertise!)
- Be willing to work in a team and to learn from others
- Commit to the programme schedule and expect to spend 13-16h per week on this programme.
- Be ready to work on your foundations to build the necessary prerequisites using the resources linked below in the run up to the programme!
Does this sound like you? Make sure to apply!
The Application at a Glance
The application process for BeyondAI consists of three stages. In the first stage you complete and submit a formal application. The second stage is the Preparation Stage, where you'll work with our preparation material on maths, programming, AI and LaTeX independently, and document your learning journey. The last week of the Preparation Stage marks the third and last stage of the application process. You'll be asked to complete and submit a set of challenges showing us what you have learned.
⚠️ At no stage of the application process do we permit the use of AI. ⚠️
Application
For the application you'll be asked to write a motivation letter (no AI!), so we can get to know you and why you think you are a good fit for the programme. You will also have to complete a detailed schedule in Google Calendar showing us that you will be able to balance the programme with your other commitments. (Check out our detailed programme schedule!) Finally, you will have to submit both documents through our application form.
Preparation
After passing the first round you will be invited to our Preparation Stage. (Notifications will be send by email, so check your spam!) For four weeks you will be working with our preparation material and document your learning journey. This will help you to build the necessary foundations in math, AI, programming in Python and LaTeX. It will show us how committed you are to learning and our programme. Your Learning Journey starts here!
Show us!
Show us you are ready for the programme! At the beginning of the third week of the Preparation Stage you'll be emailed a set of challenges. They will be based on the preparation material we'll have shared with you. Expect problems in maths, programming in Python and AI. We are not just interested in the final answers, but also in your reasoning and how you got them. You will record and submit your explanations as a video. It's time to show us what you have learned!
*Psst*... For you!
We have curated this beautiful Notion Page for you to kick-start your adventure right now and get ready for the programme!
We expect you to go over these resources no matter whether you are more experienced, or a beginner. It’s essential for a successful application for the programme.
Watch this space, as we will keep updating this Notion page!
Some of our student's testimonials...
“Overall I really liked the way the programme was structured. I liked how the knowledge gained from each session felt connected. Overall I also really liked the teaching and intuition of the topics taught. It made AI as a concept feel more approachable. I remember looking up some these topics prior the programme and feeling intimidated. But the way it was taught here felt very natural, and was much easier to understand.”
Karuna P. Inaugural Cohort 2024
“The BAI program stands out from almost every other program because of its unique teaching style. Dr. Bar is an amazing mentor and teacher, he doesn’t just spoonfeed us all the content but lets us think for ourselves. I benefited a lot from his sessions, and also from the consolidation exercises at the end of sessions.”
Warenya K. A. Inaugural Cohort 2024
Want more information?
No Boundaries. Just Breakthroughs. Join BeyondAI — the Research Programme Redefining What’s Possible! - Edited by Louila J. (Alumni)
Instruction Video - How to Apply to BeyondAI?
Some of Our Former Mentors!
Dr. Devendra Singh Dhami
Dr. Dhami currently works as an Assistant Professor in the Uncertainty in Artificial Intelligence group at Eindhoven University of Technology. He received his PhDs from the University of Texas at Dallas, and Indiana University Bloomington, in Artifical Intelligence and Computer Science respectively. He is interested in the intersection of causality and neuro-symbolic AI where the causal models inform neuro-symbolic models and vice versa in order to learn better systems.
Dr. Helena Bahrami
Full-time Artificial Intelligence and Machine Learning Team Leader at Wine-Searcher. Dr. Bahrami received her PhD at Auckland University of Technology, and has experience working as an AI Research Scientist. She is interested in brain-like and quantum-inspired hybrid deep learning models for Spiking Neural Networks.
Dr. Filip Bar
Founder. CEO and Lead Educator of ThinkingBeyond. Dr. Bar got his PhD from Cambridge, he is a qualified teacher of maths and physics with more than six years of teaching experience, and is currently affiliated with Lund University doing research in Synthetic Differential Geometry, Infinitesimal Algebra and its applications to Classical Field Theory.
Adeyemi Damilare Adeoye
PhD student in Computer Science and Systems Engineering researching optimization at IMT Schoolf for Advanced Studies Lucca. He holds a Master degree in Machine Intelligence, and in Mathematical Sciences. He is interested in optimization for machine learning and engineering applications, as well as data-driven identification and control of complex dynamical systems.
Matthew Pugh
Machine Learning Research PhD student at University of Southampton. He is interested in applied category theory, Kan extensions and enriched category theory. He also holds a degree in mechatronic engineering.
Emilie Gregoire
PhD student in the Data Analytics Laboratory at Vrije Universiteit Brussel. She holds a Master’s degree in Physics and Astronomy, and has taught various courses in Informatics and Data Science at the Faculty of Economics at Vrije Universiteit. Her research interests include multi-task learning, theoretical aspects of deep learning, learning dynamics, and recurrent neural networks.
Barbora Barancikova
PhD student at the AI4Health Doctoral Training Centre at Imperial College London, specialising in rough path theory, a mathematical framework for extracting insights from time series data. Much of her research focuses on deep learning, generative modelling, and their applications in healthcare and finance. Recently, she has been working on diffusion models for time series generation. She also holds a degree in Mathematics and Computer Science from the University of Glasgow.
Matej Cief
PhD student at Kempelen Institute of Intelligent Technologies, researching off-policy evaluation and learning of multi-armed bandits. He is interested in reinforcement learning from human feedback and how to evaluate LLMs without collecting new preference data. He has a Master’s in software engineering and completed two science internships at Amazon.