| Course | Number of hours | ECTS points | Form of verification | Obligatory |
|---|---|---|---|---|
|
Laboratory classes: 15 Lecture: 30 |
5 | Graded assignment | Obligatory |
|
Laboratory classes: 30 Lecture: 30 |
6 | Exam | Obligatory |
|
Laboratory classes: 30 Lecture: 30 |
6 | Graded assignment | Obligatory |
|
Laboratory classes: 25 Lecture: 30 |
5 | Graded assignment | Obligatory |
|
Laboratory classes: 15 Lecture: 15 |
3 | Graded assignment | Obligatory |
|
Lecture: 15 |
2 | Graded assignment | Obligatory |
|
Lecture: 15 |
3 | Graded assignment | Obligatory |
| Sum | 280 | 30 |
Study programme Artificial Intelligence and Machine Learning
A graduate of the Artificial Intelligence and Machine Learning program possesses strong theoretical foundations in machine learning, deep neural networks, reinforcement learning, advanced data processing, and knowledge representation. They also have practical skills enabling them to solve real-world, complex problems and to design and implement intelligent systems for real operational environments. Graduates are creative in proposing new analytical methods, system implementations, and applications that support or replace human work. They understand current AI trends, can formulate and verify research hypotheses, and are well prepared for employment in the rapidly evolving international job market as well as for continuing studies at the doctoral level. The program aligns with the strategic mission of Lodz University of Technology, which emphasizes advancing knowledge, conducting scientific research, and educating highly qualified professionals. By focusing on advanced methods of information analysis and processing, combined with the ability to leverage fast‑moving technological progress, the program supports the development of a competitive, knowledge‑based economy. Establishing this program directly fulfills the University’s mission and strategic goals by developing intellectual capacity essential for innovation and regional and national competitiveness.
Chair of the Programme Board: prof. dr hab. inż. Krzysztof Ślot
The programme was approved by Senate Resolution No. 104/2025 of 17 December 2025.
| Course | Number of hours | ECTS points | Form of verification | Obligatory |
|---|---|---|---|---|
|
Laboratory classes: 10 Lecture: 25 |
5 | Exam | Obligatory |
|
Project work: 20 Lecture: 30 |
5 | Graded assignment | Obligatory |
|
Laboratory classes: 21 Project work: 24 Lecture: 30 |
6 | Exam | Obligatory |
|
Laboratory classes: 10 Project work: 25 Lecture: 20 |
5 | Graded assignment | Obligatory |
|
Laboratory classes: 30 Lecture: 15 |
3 | Graded assignment | Obligatory |
|
Project work: 30 Lecture: 30 |
6 | Graded assignment | Obligatory |
| Sum | 320 | 30 |
| Course | Number of hours | ECTS points | Form of verification | Obligatory |
|---|---|---|---|---|
|
Laboratory classes: 10 Project work: 15 Lecture: 30 |
5 | Graded assignment | Obligatory |
|
Laboratory classes: 45 Lecture: 15 |
6 | Graded assignment | Obligatory group |
| The Student chooses 1 subjects | ||||
Analytical processing – Big Data
|
Laboratory classes: 45 Lecture: 15 |
6 | Graded assignment | Optional |
|
Laboratory classes: 45 Lecture: 15 |
6 | Graded assignment | Optional |
|
Total number of contact hours: 40 |
5 | Graded assignment | Obligatory group |
| The Student chooses 1 subjects | ||||
Human-AI Collaboration Systems
|
Laboratory classes: 4 Project work: 21 Lecture: 15 |
5 | Graded assignment | Optional |
|
Laboratory classes: 15 Project work: 10 Lecture: 15 |
5 | Graded assignment | Optional |
|
Laboratory classes: 20 Project work: 30 Lecture: 20 |
7 | Graded assignment | Obligatory group |
| The Student chooses 1 subjects | ||||
Signal Analysis Fundamentals
|
Laboratory classes: 20 Project work: 30 Lecture: 20 |
7 | Graded assignment | Optional |
|
Laboratory classes: 20 Project work: 30 Lecture: 20 |
7 | Graded assignment | Optional |
|
Tutorials: 45 |
2 | Graded assignment | Obligatory subjects to choose from |
|
Project work: 15 |
5 | Graded assignment | Obligatory |
| Sum | 285 | 30 | ||
| Course | Number of hours | ECTS points | Form of verification | Obligatory |
|---|---|---|---|---|
Research Project
|
Project work: 8 Lecture: 2 |
4 | Pass | Obligatory |
|
Seminar: 30 |
3 | Exam | Obligatory |
|
Laboratory classes: 15 Lecture: 10 |
3 | Graded assignment | Obligatory |
|
Diploma Thesis: 0 |
20 | Pass | Obligatory subjects to choose from |
| Sum | 65 | 30 |