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This master's program is designed to meet the growing need for data science professionals who can create advanced computational intelligence solutions, processing vast quantities of complex information to guide corporate strategies and market decisions.
A core focus of the curriculum is automated big data analysis and knowledge extraction using machine learning, neural networks, and evolutionary computation methods.
Students will learn to implement state-of-the-art machine learning approaches for large-scale data analysis, evaluate the statistical relevance of data mining outcomes, and execute sophisticated data mining operations. The program introduces essential frameworks like Hadoop MapReduce, Spark, relational databases, and NoSQL systems, paired with user-friendly yet robust development environments including Python and R.
We explore evolving concepts, methodologies, and administration of distributed intelligent computing systems through diverse case studies showcasing real-world implementations, such as color steganography detection systems. The curriculum emphasizes practical applications of data science methodologies integrated with computational intelligence for data-centric problem-solving, including complex data analysis, interpretation, and visualization - skills increasingly sought after in sectors like marketing, pharmaceuticals, finance, healthcare, logistics, and business administration.
Participants may pursue an optional work placement2 to enhance their practical expertise and career readiness. Additional module details are available.
1 year full-time