“Data Science and Artificial Intelligence” master programme


“Data Science and Artificial Intelligence” master programme at the Faculty of Informatics at Titu Maiorescu University (TMU), has been accredited by the Romanian Agency for Quality Assurance in Higher Education – ARACIS. (Decisions 30.06.2022 – ARACIS)


“Data Science and Artificial Intelligence” master programme is defined by its innovative, creative, interdisciplinary nature, its applied vocation, and its focus on the development of solid professional competencies. By increasing the level of qualification, the master programme aims to promote and provide high-quality practical training to students in this future-oriented field for the workforce in Romania and Europe, which will have a highly positive impact on improving the quality of life for European citizens.


“Data Science and Artificial Intelligence” master programme is a full-time program and is a professional master programme in the field of Informatics (2 years, 120 credits).


The courses and laboratories will be conducted in a hybrid system, in modules, usually at the end of the week (Friday-Saturday-Sunday), and specialized practical work will be carried out in modern computer laboratories with hands-on practical applications in the cloud (AWS) or on the TMU research platform with Apache Spark and Databricks.


The program is conducted according to European standards of academic quality, benefiting from professors and specialists in the field, ensuring exceptional study conditions. The lecture halls and laboratories are located in Buildings M and V at  TMU, equipped through the UpDigitalUTM project, worth over 2.5 million euros from the National Recovery and Resilience Plan (PNRR).


Moreover, all Master’s students will have free access to specific professional courses in the field through the Coursera for Campus platform, with over 3,000 courses available and AWS Academy.


The program adopts new methods and approaches in the teaching process, focusing on the students, the competencies acquired, and the results. It emphasizes the quality of education, partnerships with top universities and companies in the EU, UK, and US, internships in renowned institutions and companies in various fields of activity, prospects for integration into the job market after graduation, and opportunities for personal and professional development, including doctoral studies. These are essential arguments in favor of undertaking this Master’s program.

The proposed master programme is aimed at graduates of bachelor’s studies in various fields of activity that have a foundation in computer science, process large volumes of data, use artificial intelligence or robotics, and engage in digital transformation projects/programs. Examples of such fields include:

  • Cybernetics, Mathematics
  • Computer Science, Electronics, and Communications
  • Applied Technical Sciences
  • Economics, Finance, Banking
  • Management, Administration, Business
  • Psychology, Sociology
  • Medicine
  • Law
  • Natural Sciences
  • Political Science and Communication

Other graduates from related faculties who wish to deepen their knowledge in the field of the Master’s program.


The professional competencies acquired by graduates of  “Data Science and Artificial Intelligence” master programme will enable them to:

  • Deepen their theoretical and practical understanding of the fundamental concepts and paradigms of data science and artificial intelligence.
  • Collect, analyze, and visually represent data, extract insights from data, and build models.
  • Use programming languages and software dedicated to the fields of data science and artificial intelligence.
  • Operate with fundamental concepts in mathematical modeling and statistical analysis, and apply them in practical contexts.
  • Understand the basic mechanisms and techniques of text analysis for addressing essential aspects of natural language processing.
  • Utilize technologies, software applications, and specific platforms for processing large volumes of data with enhanced cybersecurity measures.
  • Work with distributed computing platforms available as cloud services.
  • Have knowledge of national and EU norms and regulations in the field of data science and artificial intelligence.





  • Foundations in Data Science and Artificial Intelligence
  • Python Programming
  • Applied Statistics in Data Science and Artificial Intelligence
  • Advanced Data Structures
  • Data Mining and Machine Learning
  • Data Collection and Manipulation Techniques


  • Information Theory and Applications
  • Applied Bayesian Methods
  • Cloud Computing for Data Analysis
  • Computer Vision


  • R Programming




  • Artificial Intelligence and Robotics
  • Deep Learning
  • Natural Language Processing (NLP) and Text Mining
  • Ethics and Academic Integrity
  • Specialized Internship
  • Dissertation Development


  • Big Data
  • Blockchain Technologies
  • Business Intelligence
  • Data Encoding and Compression
  • Cybersecurity in Data Science and Artificial Intelligence
  • Software Engineering


  • Reliability and Testing of Computing Systems