Where the Talent and Opportunity Converge

Prove your skills, showcase your talent, and enhance your proficiency and experience in Data Analytics, Machine Learning, and AI.

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Learn in our Datathon Join our lab Cooperate with us

Digital Talent Lab at MUNI: Your Gateway to Data Analytics, Machine Learning, and AI Mastery

Open to students, professionals, and enthusiasts in Data Science, Data Analytics, Machine Learning, and AI tools.
Run by the Digital City Lab at the Institute of Computer Science, MUNI.
Guided by researchers from Professor Stan Sobolevsky team during the Datathon.
A hands-on 'Datathon' event solving real world projects handling big data.
Merges Computer Science, mathematics, Data Analytics, Machine Learning, and AI for innovation.
Access to cutting-edge tools to handling data in multidisciplinary research.
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A New Path to Data-Driven Excellence

“As generative AI reshapes coding, demand shifts from speed to insight. Skilled developers leveraging AI can build complex systems up to 80x faster. The future belongs to those who think beyond the code.”

Stan Sobolevsky
Head of the Digital City Lab
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“We offer a unique opportunity for those eager to expand their qualifications and develop a data-driven mathematical mindset—the ability to think mathematically about real-world data and work with it in a sophisticated way.”

Jan Slovák
Mathematician and researcher
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“In Datathon, participants will examine the dataset, perform initial data cleaning, explore potential analytical approaches, and formulate preliminary hypotheses or solutions. They will be challenged to solve specific problems using real-world datasets, building upon their initial explorations. We are there to mentor them when they examine datasets to identify trends and draw conclusions, often using specialized software and systems.”

Daniel Bretsko
Founding Engineer (AI/ML) at Meetsta and Deep Learning Researcher at MUNI
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“At Digital City Lab, we unfold the complexity of urban systems to drive cutting-edge research, innovation, and real-world applications. By leveraging big urban data, AI, and network science, we make cities smarter, more efficient, and sustainable—creating better places to live, concluded Khulbe, the Deep Learning researcher with a focus on graph AI models and their applications in large scale urban networks.”

Devashish Khulbe
Deep Learning researcher with a focus on graph AI models and their applications in large scale urban networks

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