EEML Summer School 2026 – Fully Funded Program in Montenegro

The Eastern European Machine Learning (EEML) Summer School 2026 is a prestigious, fully funded educational program focused on Artificial Intelligence (AI) and Machine Learning (ML). This six-day intensive summer school will be held in Cetinje, Montenegro, from 27 July to 1 August 2026.

The program combines theoretical lectures, practical workshops, and hands-on coding sessions, giving participants a comprehensive understanding of machine learning concepts. Topics include deep learning, reinforcement learning, neural network architectures, AI model evaluation, and research best practices.

Participants will have the opportunity to interact with leading AI researchers, present their own ideas, and network with peers from around the world, fostering collaboration and career growth in AI and ML fields.

Eligibility:

  • Open to individuals 18 years or older from any country.
  • Participants can be high school students, undergraduates, graduate students, PhD candidates, or postdocs.
  • Applicants from diverse academic or professional backgrounds in science, technology, engineering, mathematics (STEM), or related fields are encouraged to apply.
  • Strong interest in machine learning and AI research is required.

Benefits:

  • Fully funded program covering registration, accommodation, and travel expenses.
  • Access to cutting-edge AI and ML workshops led by international experts.
  • Certificate of participation upon completion.
  • Networking opportunities with global researchers, AI enthusiasts, and peers.
  • Exposure to practical AI projects and hands-on coding experience that can strengthen your research and career profile.

Deadline:
31 March 2026

How to apply:
Applicants must submit their application through the official EEML Summer School website
The application typically requires personal information, academic background, motivation letter, and optionally prior experience in machine learning or programming. Early applications are encouraged due to limited spots.


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