About the programme


Mode of study and length of the programme in years: Full-time, 4 years

Length of the degree programme in ECTS credits: 240 credits

Language(s) of instruction: Lithuanian/ English

Degree and/or Qualification awarded: Bachelor of Mathematical Sciences


Data Science is a new very fast growing data analysis science field. It connects modern and classical methods of statistics (stochastic modeling, data mining) with advanced Information Technologies (neural networks, database management).
Amount and variety of accumulated data is growing every day along with very fast developing Information technologies. As a result, specialists of data analysis are getting highly demanded.

It's worth studying because:

  • There is a great demand for Data Analysts in Lithuania and abroad; according to the the most wanted employees list (made by „Career Cast“ at 2018) specialists in statistics are on the 5th position, and Data Analysts specialists are on the 7th position. In the US Data science was evaluated as the most promising profession three years in the row (2016-2018) according Glassdoor Job Score index.
  • Data Analysis specialist has skills in the fields of data analysis, mathematical modeling and modern technologies;
  • During study period students can spend 50% of the time studying abroad;
  • This study programme has a wide list of optional modules, which help to see different fields of skills usage;
  • This programme has international level scientists as teachers;
  • Opportunity to have a practical experience at the private companies or governmental institutions in Lithuania or abroad.

Career opportunities:

Graduates of this study program have excellent career opportunities. Graduates of the program are ready to work in companies that analyze large data, provide statistical analysis services, information technology companies, whose activities are related to data analysis: banks, Exacaster, Scope Baltija, Nielsen, CGI Lithuania, Department of Statistics, STI, Bank of Lithuania.

International studies and internship opportunities:

Vilnius University encourages the use of various opportunities for studying at foreign universities, allowing students to gain intercultural experience, develop and evaluate their competences, establish contacts abroad, and open wider career opportunities.

Study plan

Course title

Credits

Course title

Credits

1 SEMESTER

30.0

6 SEMESTER

30.0

Compulsary Modules

 

Compulsary Modules

 

Basics of Mathematics

5.0

Data Science Project - Coursework

10.0

 Algebra I

5.0

Probabilistic Machine Learning Algorithms I

5.0

 Informatics

10.0

Time Series

5.0

 Introduction to Specialty

5.0

Regression Analysis

5.0

 Foreign Language

5.0

Optional Modules

5.0

 

 

Elective course units from the list:

 

2 SEMESTER

30.0

Statistical Modeling

5.0

Compulsary Modules

 

Sampling Methods

5.0

 Mathematical Analysis I

10.0

Advanced Database Management Systems

5.0

 Algebra II

5.0

Financial Intelligence

5.0

 Research Data Analysis

5.0

Risk Management

5.0

 Data Structures and Algorithms

5.0

Statistical Models in Medicine

5.0

Basics of DBMS

5.0

7 SEMESTER

30.0

 

 

Compulsary Modules

 

 

 

Probabilistic Machine Learning Algorithms II

10.0

3 SEMESTER

30.0

Applied Multivariate Analysis

5.0

Compulsary Modules

 

 

 

Mathematical Analysis II

5.0

Optional Modules

 

 Probability Theory

5.0

Elective course units from the list:

 

 Algorithm Theory

5.0

Data Tidying and Transformation with R

5.0

 Object Programming

5.0

Categorical Data Analysis

5.0

 GUS*

5.0

Optimization Methods

5.0

4 SEMESTRAS

30.0

Basics of Artificial Intelligence

5.0

Compulsary Modules

 

Natural Language Processing

5.0

 Stochastic Processes

5.0

Software Engineering

5.0

Parametric Statistics

5.0

Financial Econometrics Modeling

5.0

Data Visualization

5.0

Functional Data Statistics

5.0

Optional Modules

 

Bayesian Statistics

5.0

Elective course units from the list:

 

Censored Sampling Analysis

5.0

Statistical Modeling

5.0

 

 

Sampling Methods

5.0

8 SEMESTER

30.0

Financial Intelligence

5.0

Compulsary modules

 

Statistical Data Theory

5.0

Professional Internship

15.0

GUS*

5.0

Bachelor's Thesis

15.0

5 SEMESTER

30.0

 

 

Compulsary Modules

 

 

 

Linear Models

5.0

 

 

Nonparametric Statistics

5.0

 

 

Big Data Software Tools

5.0

 

 

Optional Modules

5.0

 

 

Elective course units from the list:

 

 

 

Data Tidying and Transformation with R

5.0

 

 

Categorical Data Analysis

5.0

 

 

Optimization Methods

5.0

 

 

Numerical Methods

5.0

 

 

Advanced Database Management Systems

5.0

 

 

Programming OS UNIX

5.0

 

 

Software Engineering

5.0

 

 

Basics of Artificial Intelligence

5.0

 

 

Natural Language Processing

5.0

 

 

GUS*

5.0

 

 


GUS* -  General University Studies. Developed competences depend on the subject chosen by a student.

Expected Learning Outcomes:

This program graduates will be able to:

  • apply the main results of different fields of mathematics;
  • create and solve practical tasks in mathematical language using right software tools;
  • select and modify data stored in relational (and non-relational) databases; to create simple relational database;
  • to collect data from various data source; evaluate the reliability of data; classify data by  source, volume, frequency and flow; organize and prepare data for analysis;
  • to identify main and secondary problems in solving analytical and practical tasks;
  • to evaluate the limitations of data analysis methods and results;
  • to select and apply the appropriate methodology for the data analysis task by selecting right software tools;
  • to evaluate suitability and reliability of the model created for the data analysis task;
  • to interpret the results of analysis, to select meaningful information and to make suggestions based on it;
  • to prepare small projects based on  data analysis; create small data analysis reports tools.

Contacts

Do you have any questions? Contact:

  • Email:
  • Phone: +370 5 219 3055
  • Address: Naugarduko str. 24, room 106, Vilnius, Lithuania