| According to the World Economic Forum’s report “The Future of Jobs 2023”, the adoption of technology will remain a key driver of business transformation over the next five years. Among these technologies, Big Data, cloud computing, and artificial intelligence (AI) show a high likelihood of adoption, with over 75% of surveyed companies aiming to implement them in the near future. The report identifies three job families that are expected to experience the most significant growth in the future: (1) Data Analysts and Scientists, Big Data Specialists, and Business Intelligence Analysts; (2) AI and Machine Learning Specialists; (3) Cybersecurity Specialists. |
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| In this context of technological transformation, labor market disruptions, and significant changes in the skills sought by companies, ISCAC has developed a Bachelor’s Degree in Data Science for Management. This program aims to address the current and future needs of the market, training students with advanced technological expertise combined with a solid foundation in business management.
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The Bachelor’s Degree in Data Science for Management is a program that develops essential skills for today’s information-driven society, enabling a meaningful understanding of business through data analysis. With a multidisciplinary approach, this degree combines principles and practices from technology, information systems, statistics, artificial intelligence, and computer engineering to analyze large datasets (Big Data). This analysis helps address key questions such as: What happened? Why did it happen? What is likely to happen? What can we do with the results?
The program emphasizes a hands-on approach and pedagogical methodologies that encourage student-driven discovery and investigation, such as project-based learning and problem-based learning. These methods aim to solve real-world challenges using appropriate datasets, fostering practical skills and critical thinking.
Course information
| DGES Code | L310 |
| Duration | 3 years |
| Regime | Full time, face-to-face teaching, daytime schedule |
| ECTS | 180 credits |
| Scientific Board | Fernando Paulo dos Santos Rodrigues Belfo (Course Coordinator) Clara Margarida Pisco Viseu Bruno José Machado de Almeida |
| Curricular Structure | Programme of Curricular Units
Goals, Learning and Teaching Methodology, Bibliography and Regime/Evaluation System Programme approved by “Despacho n.º 80/2024, de 18-12-2023, DR n.º 4, 2ª série, de 05-01-2024″ |
| Documents | Enrolment, Accreditation, Professional Goals |
| Statistical Data | https://infocursos.mec.pt |
| Access and Admission | |
| Admission Exams | One of the following: 16 Mathematics or 19 Mathematics A or 04 Economics 16 Mathematics |
| Minimum grades | Application Grade: 95 points Admission Exams: 95 points |
| Calculation formula | High school average: 65% Admission Exams: 35% |
Key Points