Informatics and Econometrics
Basic information:
- studies in the field of: Informatics and Economic Analysis
- name of the programme: Informatics and econometrics
- studies: part-time second-cycle programme, track: general academic
- leading discipline: economics and finance
Second-cycle studies in Informatics and econometrics combine education in economics, finance and business with competences in the area of modern technologies and information technology.
In second-cycle studies, Informatics and econometrics students enhance their knowledge of economics, finance and information technology. They improve their skills in data analysis (also Big data), modelling and forecasting, programming and operating IT systems and statistical packages. They explore the secrets of investing and risk management, learn about advanced database technologies and issues related to artificial intelligence, including machine learning and data science in general.
Second-cycle graduates in Informatics and econometrics can work as:
- an analyst of economic processes in organizations where business decision-making needs to be preceded by in-depth quantitative analyses with the use of information technologies;
- an IT manager who is able to work creatively and efficiently in Economy 4.0 on an international scale;
- a specialist in the field of IT solutions, a leader of project teams;
- an information broker, designer of IT solutions for business, designer of websites and network services, specialist in IT audit;
- a specialized analyst using their knowledge and skills of modelling and forecasting economic and financial quantities, and of financial-instrument valuation (quant).
Second-cycle graduates can continue their education at the Doctoral School or in postgraduate studies.
| Subject | Number of hours | ECTS points | Form of verification | Code | Block |
|---|---|---|---|---|---|
|
Multidimentional analysis
|
Lectures:
18 Classes: 18 |
5 | Exam | 1 | B |
|
Marketing
|
Classes:
18 |
2 | Assessment | 1 | A |
|
Survey sampling
|
Classes:
18 |
3 | Assessment | 1 | B |
|
Multimedia in business
|
Lectures:
18 |
3 | Assessment | 1 | B |
|
Discrete optimization
|
Lectures:
9 Classes: 9 |
3 | Assessment | 1 | B |
|
Forecasting and simulation
|
Lectures:
18 Classes: 18 |
5 | Exam | 1 | A |
|
Management information systems
|
Lectures:
18 Classes: 18 |
5 | Exam | 1 | B |
|
Management
|
Lectures:
18 Classes: 9 |
4 | Assessment | 1 | A |
| Sum | 207 | 30 | |||
| Sum (Lectures) | 99 | ||||
| Sum (Classes) | 108 |
| Subject | Number of hours | ECTS points | Form of verification | Code | Block |
|---|---|---|---|---|---|
|
Statistical analysis in marketing research
|
Classes:
18 |
2 | Assessment | 1 | C |
|
Information system analysis
|
Lectures:
9 Classes: 18 |
4 | Exam | 1 | B |
|
Time series analysis
|
Classes:
18 |
2 | Assessment | 1 | C |
|
Mathematical economics
|
Lectures:
18 Classes: 9 |
4 | Exam | 1 | B |
|
History of economics thought
|
Lectures:
18 |
3 | Exam | 1 | A |
|
Software engineering
|
Classes:
18 |
3 | Assessment | 1 | C |
|
Diploma seminar
|
Seminars:
9 |
1 | Assessment | 1 | C |
|
Elective courses I
|
Lectures:
18 |
3 | Assessment | 5 | B |
|
Elective courses II
|
Lectures:
18 |
3 | Assessment | 5 | B |
|
Advanced database technology
|
Classes:
18 |
2 | Assessment | 1 | B |
|
Information management
|
Lectures:
18 |
3 | Exam | 1 | C |
| Sum | 207 | 30 | |||
| Sum (Classes) | 99 | ||||
| Sum (Lectures) | 99 | ||||
| Sum (Seminars) | 9 |
| Subject | Number of hours | ECTS points | Form of verification | Code | Block |
|---|---|---|---|---|---|
|
IT Tools for Data Visualization
|
Lectures:
9 |
1 | Assessment | 1 | B |
|
Actuarial methods
|
Lectures:
9 Classes: 18 |
4 | Exam | 1 | A |
|
Designing multimedia application
|
Classes:
18 |
4 | Exam | 1 | C |
|
Specialitsation elective I
|
Lectures:
18 |
3 | Assessment | 5 | C |
|
Przedmiot specjalnościowy II do wyboru
|
Lectures:
18 |
3 | Assessment | 5 | C |
|
Specialitsation elective III
|
Lectures:
18 |
3 | Assessment | 5 | C |
|
Specialitsation elective IV
|
Lectures:
18 |
3 | Assessment | 5 | C |
|
Diploma seminar
|
Seminars:
9 |
4 | Assessment | 1 | C |
|
Machine Learning
|
Lectures:
9 Classes: 9 |
2 | Assessment | 1 | B |
|
Elective courses III
|
Lectures:
18 |
3 | Assessment | 5 | B |
| Sum | 171 | 30 | |||
| Sum (Lectures) | 117 | ||||
| Sum (Classes) | 45 | ||||
| Sum (Seminars) | 9 |
| Subject | Number of hours | ECTS points | Form of verification | Code | Block |
|---|---|---|---|---|---|
|
Big Data
|
Classes:
18 |
3 | Assessment | 1 | B |
|
Law
|
Lectures:
9 |
2 | Assessment | 1 | A |
|
Specialitsation elective V
|
Lectures:
18 |
3 | Assessment | 5 | C |
|
Diploma seminar
|
Seminars:
18 |
10 | Assessment | 1 | C |
|
Monte Carlo simulations in economics
|
Classes:
18 |
3 | Assessment | 1 | C |
|
Elective courses IV
|
Lectures:
18 |
3 | Assessment | 5 | B |
|
Wykład kierunkowy w języku obcym do wyboru - konwersatorium
|
Lectures:
18 |
3 | Assessment | 5 | D(B) |
|
Wykład ogólny do wyboru
|
Lectures:
18 |
3 | Assessment | 5 | A |
| Sum | 135 | 30 | |||
| Sum (Classes) | 36 | ||||
| Sum (Lectures) | 81 | ||||
| Sum (Seminars) | 18 |