Summer School of Machine Learning

We invite interested university students to apply for the 10th international school “Practical Seminar In Machine Learning” (PSIML) which will be held from 26th July to 5th August 2024 at the Students’ Resort Palić.

About our program

For whom

The PSIML Summer School is designed for anyone with a keen interest in Machine Learning, irrespective of their academic year or faculty major. Prerequisites for PSIML are your enthusiasm to delve deep into the world of Machine Learning and basic knowledge of Python and Math. The school offers unique opportunities to learn first hand through various exercises, lectures and discussions and also to apply that knowledge through intriguing projects, all under the guidance of experienced mentors. Additionally, you will have access to the necessary computational resources for the project. It’s not all work; you will also get to meet peers and lecturers who share the same passion for Machine Learning. If you are looking to spend 10 days of your summer gaining knowledge, experience while also have great time within the Machine Learning community, PSIML is the perfect fit for you.

By whom

We are gathering Machine Learning experts from various backgrounds, including both accomplished academic researchers and professors, and also experienced industry engineers. A shared passion for Machine Learning and a desire to impart their knowledge to the next generation unites us all. Our lecturers and mentors are highly approachable and always eager to answer questions and provide the necessary guidance to all students. The voluntary nature of our work highlights the commitment and enthusiasm of all our organizers in making PSIML the platform for knowledge transfer and advancement in the field of Machine Learning. Many of our organizers are PSIML alumni, which emphasizes the impactful role that PSIML has had for them.

Our aim

At PSIML, our mission is to create a learning environment that fosters rapid knowledge acquisition. We believe that interactive, face-to-face lectures hold significant value that cannot be achieved through online materials. By offering opportunities for both theoretical and practical work, we ensure a well-rounded understanding of many parts of Machine Learning. Our curriculum covers a wide range of topics, from fundamental concepts to the latest breakthroughs in ML. However, the most enriching aspect of PSIML might be the opportunity it offers for networking. It allows students to meet new people, share insights and experiences, and become a part of the (PSI)ML community.

How to apply

Topics

  • Machine Learning Basics
  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning
  • Convolutional Neural Networks
  • Transformers
  • Graph Neural Networks
  • Random Classification
  • Regression Forests
  • Generative models
  • Computer Vision

Contact us