ML Week is an intensive educational and practical platform that brings together the best young talents from leading universities in Ukraine (NULP, KhPI, KPI, OP) to solve real-world problems using machine learning.

The event aims to create a community of future leaders in the field of artificial intelligence who, collaborating with each other, develop innovative solutions for business, science, and society.

 

MISSION

To inspire, unite, and create conditions for the development of future leaders in the field of machine learning, promoting innovation and progress in Ukraine.

 

GOAL

Deepening knowledge in the field of machine learning (ML):

• Introducing participants to modern methods, algorithms, and approaches in Computer Vision and Data Science.
• Practical application of ML to solve real-world problems.

Development of practical skills:

• Using current ML tools and libraries (Python, TensorFlow, OpenCV, Scikit-learn).
• Building a full cycle of an ML project: from data preparation to model deployment.

Formation of interuniversity teams:

• Creating conditions for working in mixed teams, which promotes the exchange of knowledge and experience.
• Development of soft skills: improving teamwork, leadership, time management, and communication skills within projects.

Developing solutions for real problems:

• The tasks are aimed at creating ML solutions that can be integrated into production, business, or social processes.

Familiarity and use of current trends in ML:

• deep learning,
• data analysis,
• object detection, etc.

Talent support:

• identifying promising participants for further involvement in research projects or cooperation with partner companies.
• recognition of achievements through awards for the best projects and teamwork.

Strengthening ties between universities:

• Building partnerships between NULP, KhPI, KPI and OP.

Partnership expansion:

• Communication with experts, teachers, and industry representatives who may become mentors or partners in the future.

 

RESULTS

• Participants will master the theoretical and practical aspects of ML.
• Participants acquire practical skills necessary for work in the IT industry or research centers.
• The developed projects can be presented as examples in a CV or portfolio and can be integrated into production or research initiatives.
• Participating universities establish contacts for future projects.