Master of Science Artificial Intelligence & Data science for Business

Program Overview

The Master of Science in Artificial Intelligence & Data Science for Business program equips graduates with the skills to design and implement AI and data science solutions for business challenges. The program emphasizes hybrid skills, ethical considerations, and the ability to lead innovation projects in a VUCA environment. Graduates are prepared for careers in fields such as machine learning engineering, data science, and AI consulting.

Program Outline

Degree Overview:

Overview:

The Master of Science in Artificial Intelligence & Data Science for Business program prepares graduates to meet the challenges and exploit the potential of data and artificial intelligence in business and society.

Objectives:

• Develop graduates capable of designing and implementing computer programs to accelerate business performance and drive industry transformation.
• Train graduates to contribute to the progress of humanity in various fields while ensuring ethical considerations evolve alongside technical and societal developments.
• Equip graduates with the skills to lead innovation projects, support organizational transformation, and mobilize technological and scientific knowledge integrated with business or professional management logics.

Description:

The program focuses on fostering hybrid skills, enabling graduates to lead multidisciplinary groups and connect the scientific dimensions of AI and data science to business and society through open, collaborative, and frugal innovation. Students develop an ability to act in a VUCA environment (vulnerable, uncertain, complex, and ambiguous) and embrace uncertainty in their decision-making.

Outline:

Year 1:

• Data Processing: Covers computer science, data analysis, AI technologies, programming, mathematics, and statistics.
• Business and Market Economics: Provides foundational knowledge in business, economics, and legal environments.
• AI, Ethics & Society: Explores the ethical and societal implications of AI.

Year 2:

• Data Modeling: Focuses on server and computer networks, systems architecture, machine learning, data visualization, and mathematical modeling.
• Marketing and Finance: Delves into marketing and finance concepts.
• AI Development Project Management: Equips students with project management skills for AI projects.

Year 3:

• Development of Artificial Intelligence: Covers cloud tools, information security, machine learning, deep learning, and AI ethics.
• Cost and Budget Analysis: Provides knowledge in cost and budget management.
• Human Resources Management: Explores human resources concepts.

Year 4:

• Technical Machine Learning Business Projects: Involves machine learning projects with a business focus.
• Deep Learning: Covers methods and applications of deep learning.
• Big Data in Practice: Explores the practical applications of big data.
• AI & Data Science for Marketing: Focuses on the use of AI and data science in marketing.
• AI, Ethics & Society: Delves into the ethical and societal implications of AI in the context of big data.

Year 5:

• Strategic Vision and Specialization: Students choose a specialization and complete a final project or thesis.
• Work-Study Mission Report: Involves a work-study mission related to the specialization.

Careers:

• Machine Learning Engineer
• Data Scientist
• Consultant Big Data
• Artificial Intelligence Engineer (also known as AI Project Manager, AI Project Director, AI Expert, AI Consultant)

Tuition fees:

• For those admitted to the 1st year:
• €9,500/year
• For those admitted in the 2nd year:
• €19,900/ year
• For those admitted in 3rd year
• €12, 900 / year
• Master' Degree:
• € 12, 900 / year
• For those admitted to the 4 th year
• €14 900/ year