Data Science: Computer Science Leiden University

Overview

The Data Science: Computer Science master's programme at Leiden University offers a comprehensive education at the intersection of computer science and statistical science. This interdisciplinary approach focuses on extracting valuable insights from large datasets through advanced methodologies, including data mining, machine learning, and statistical analysis. Students will gain expertise in the computational aspects of data analysis, encompassing techniques such as deep learning, network analysis, and text analytics.

Leiden University is renowned for its strong academic standing and innovative research environment. The Data Science master's specialisation is distinguished by its collaboration between the Leiden Institute of Advanced Computer Science and the Mathematical Institute, alongside the Leiden Centre of Data Science. This unique partnership enhances the programme's strength, providing students with opportunities to engage in research and collaborate with various scientific disciplines, companies, and organisations.

The tuition fees for the Data Science: Computer Science master's programme are as follows:

• International students: EUR 21,800 per year
• European students: EUR 2,601 per year

Visit the Fees and Funding section for a breakdown in your local currency.

The programme structure allows students to tailor their studies to their interests. Key areas of focus include:

• Data Mining
• Machine Learning
• Statistical Data Analysis
• Deep Learning
• Network Analysis
• Text Analytics
• Advanced Computing Systems
• Artificial Intelligence
• Foundations of Computing

Graduates of the Data Science: Computer Science programme are well-prepared for various roles in the tech industry. Alumni have found positions in leading companies and sectors, leveraging their expertise in data analysis and computational methods. Potential job roles include data scientist, machine learning engineer, and statistical analyst, among others, allowing graduates to contribute significantly to data-driven decision-making in diverse fields.