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University: Wrocław University of Technology
Category: Computer Science
Location:
Level: Master
Deadline: Mon 18 November 2024
Intake: February
Application Fee: 85 PLN
Tuition Fee: 4000 PLN
Duration: 3 Semesters
The Master's program in Big Data Analytics offered by the Wroclaw University of Technology is a two-year full-time course that equips students with the skills and knowledge required to become experts in big data analytics. The program is designed to provide a comprehensive understanding of the latest trends, technologies, and tools used in the field of big data analytics, including data mining, machine learning, natural language processing, and predictive analytics. Students will also gain hands-on experience working with big data technologies such as Hadoop, Spark, and NoSQL databases.
The Faculty of Computer Science and Management at Wroclaw University of Technology is responsible for delivering the Big Data Analytics program. The faculty has an experienced and highly qualified team of faculty members who are experts in their fields and dedicated to providing students with the best education possible. The faculty has state-of-the-art facilities and laboratories to provide students with practical experience and support their research activities. The faculty's research activities cover a wide range of topics related to computer science, including artificial intelligence, machine learning, data mining, and computer vision.
The Big Data Analytics program offered by the Faculty of Computer Science and Management at Wroclaw University of Technology is an excellent choice for students who want to pursue a career in the rapidly growing field of big data analytics. Graduates of the program are well-prepared to take on roles such as data analysts, data scientists, and big data engineers in a range of industries, including finance, healthcare, retail, and technology. The program's strong emphasis on practical skills and real-world projects ensures that students are equipped with the skills and knowledge required to succeed in today's data-driven world.