Tutors
Prof. Ciprian Turturean, PhD.
Prof. Mircea Asandului, PhD.
Curriculum
- First semester
Quality and Data Validation
Introduction to Python for Data Mining
Data Processing and Analysis Languages for Data Mining
Introduction to R
Second semester
Research Methodology
Cluster and Ranking Analysis
Decision Trees
Optional courses: 1 out of 3
Database Administration
Data Warehouses
Big Data for Machine Learning
Supplementary Courses
Accounting and information systems
Modelling
The educational plan is valid for the first year of study (2024/2025) - First semester
Neural Networks
Multiple Regression. Variance and Covariance Analysis
Logistic Regression
Optional courses: 1 out of 2
Image Processing
Statistical Processing of Text Data
Supplementary Courses
Accounting and Information Systems
Modelling
Second semester
Ethics and Academic Integrity
Master’s Thesis Preparation
Bayesian Statistics
Structural Equation Models
Scaling and Conjoint Analysis
Internship
The educational plan is valid for the 2nd year of study (2024/2025)
The need for specialists able to create and manage large databases, extract information using statistical methods and provide support for decision-making is emphasised by an increasing number of competent voices in the public sphere. Concepts such as Big Data, Data Analyst, Data Scientist, Data Mining are currently among the areas of interest of specialists from universities, research institutes and companies. At a time when computer power is growing exponentially, databases are larger and increasingly complex, which calls for specialists with mixed skills in the area of statistics and informatics, able to work in the new and dynamic conditions of the global market.
Specific Objectives
– Training high-level specialists capable to:
- Elaborate and implement databases and data storage strategies;
- Manage the structure and quality of the data relevant for an organisation, with a view to increase their value;
- Assess the methods and tools that are adequate for data analysis within specific organisational contexts;
- Apply advanced data analysis methods within a wide range of organisational environments;
- Build analysis and predictive models by using adequate tools.
– Ongoing training of the employees, in order to improve the practical experience within an organisation by using data analysis methods and specialised programme packages.
– Research development in Data Mining.
The graduates of this study programme can work in: Market research companies, (outsourcing) services companies; IT companies, Social media companies; Finance-Banking institutions; Healthcare institutions; Research centres in the private and public sector; Consultancy Firms, Companies, etc.