Master
Masters Data Science
Degree
Master
Tuition Fee
€3500
Study Format
Online
Duration
8-12 Months
Number of Courses
12 Courses
Instructor:
About the Program
Our Ph.D in Data and Cybersecurity is an advanced academic degree focusing on in-depth research, advanced methodologies, and the development of innovative strategies to protect digital systems, data, and information from unauthorized access, breaches, and cyber threats. It involves analyzing security risks, creating robust encryption methods, exploring emerging technologies, and contributing to the advancement of secure data practices through research and practical implementations. Graduates play a crucial role in securing digital infrastructures and shaping cybersecurity policies in various industries.
Program Curriculum
60 - 120 ECTS
Course Overview
Year 1 (Semester 1-2)
Quantitative Fundamentals
Data Structures and Algorithm
Programming with R and Python
Computational Statistics & Probability
Cloud Computing
AI & Humanity: The Ethics of Data Science
Year 2 (Semester 3-4)
Machine Learning
Distributed Algorithms and Optimization
Design and Analysis of Experiments
Deep Learning
Natural Language Processing
Capstone Project
Course Outcomes
By the end of the Master in Data Science program, students will be able to:
- Demonstrate Proficiency in Data Analysis: Apply advanced statistical and analytical techniques to interpret and visualize data, deriving actionable insights for decision-making.
- Utilize Machine Learning Algorithms: Leverage machine learning models and algorithms to develop predictive analytics and automate data processing tasks.
- Conduct Data Mining: Execute data mining techniques to uncover patterns and trends within large datasets, contributing to strategic business initiatives.
- Communicate Data Findings Effectively: Exhibit strong communication skills to convey complex data concepts and analytical results to both technical and non-technical audiences.
- Implement Data Management Practices: Design and implement robust data management practices, ensuring data integrity, confidentiality, and accessibility across organizational systems.
- Engage in Ethical Data Practices: Understand and apply ethical considerations surrounding data usage, compliance with regulations, and responsible data handling.
- Foster Innovation through Data-Driven Solutions: Develop innovative data-driven strategies that support organizational goals and enhance operational efficiency.
- Collaborate in Data-Driven Projects: Work effectively in interdisciplinary teams to analyze and solve complex problems, leveraging diverse skills and perspectives to achieve common objectives.