Digital chemistry
Digital chemistry
CHEMISTRY
| Course of education | 2024- 2026 | 
| Specialisation | Digital Chemistry | 
| Type of study | Second-cycle studies / Master’s study | 
| Mode of study | Full-time studies | 
| Study profile | academic | 
During each semester, the student should obtain a minimum of 30 ECTS points from obligatory and optional classes (elective)
| SEMESTER 1 | ||||||
| subject | lecture | auditorium classes | laboratory classes | TOTAL | E/P | ECTS | 
| Education health and safety (e-learning; extended course) | 
 | 5 | 
 | 5 | PWN | 0 | 
| 
 | 30 | 
 | 30 | P | 3 | |
| 
 | 30 | 
 | 30 | P | 3 | |
| 
 | 30 | 
 | 30 | P | 3 | |
| 10 | 
 | 
 | 10 | P | 1 | |
| Introduction to Python programming – lecture | 15 | 
 | 
 | 15 | E | 2 | 
| Introduction to Python programming – laboratory classes | 
 | 
 | 45 | 45 | Z | 3 | 
| Quantum chemistry in practice – lecture | 30 | 
 | 
 | 30 | E | 3 | 
| Quantum chemistry in practice – laboratory classes | 
 | 
 | 45 | 45 | Z | 3 | 
| Exploratory analysis of multidimensional chemical space – lecture | 30 | 
 | 
 | 30 | E | 3 | 
| Exploratory analysis of multidimensional chemical space – laboratory classes | 
 | 
 | 45 | 45 | Z | 4 | 
| Foreign language III | 
 | 30 | 
 | 30 | P | 2 | 
| In the first semester, students complete a compulsory library course | ||||||
| SEMESTER 1 | 85 | 125 | 135 | 345 | 3 | 30 | 
| SEMESTER 2 | ||||||
| subject | lecture | auditorium lasses | laboratory classes | TOTAL | E/P | ECTS | 
| Introduction to R programming - lecture | 15 | 
 | 
 | 15 | E | 2 | 
| Introduction to R programming – laboratory classes | 
 | 
 | 45 | 45 | Z | 3 | 
| Molecular mechanics & dynamics, coarse-grain modeling - lecture | 30 | 
 | 
 | 30 | E | 3 | 
| Molecular mechanics & dynamics, coarse-grain modeling – laboratory classes | 
 | 
 | 45 | 45 | Z | 3 | 
| Specialization lecture*: | 30 | 
 | 
 | 30 | P | 3 | 
| 
 | 
 | 180 | 180 | P | 12 | |
| Facultative course I: | 
 | 
 | 30 | 30 | P | 2 | 
| Facultative course II: | 
 | 30 | 
 | 30 | P | 2 | 
| SEMESTER 2 | 75 | 30 | 300 | 405 | 2 | 30 | 
| YEAR I | 160 | 155 | 435 | 750 | 5 | 60 | 
| SEMESTER 3 | ||||||
| subject | lecture | auditorium lasses | laboratory classes | TOTAL | E/P | ECTS | 
| Machine learning in chemistry – lecture | 30 | 
 | 
 | 30 | E | 3 | 
| Machine learning in chemistry – laboratory classes | 
 | 
 | 45 | 45 | Z | 3 | 
| 15 | 
 | 
 | 15 | P | 1 | |
| 30 | 
 | 
 | 30 | P | 2 | |
| 
 | 
 | 180 | 180 | P | 10 | |
| 
 | 30 | 
 | 30 | P | 4 | |
| Monographic lecture*: | 30 | 
 | 
 | 30 | P | 3 | 
| Facultative course III: - Insights into reaction mechanisms and kinetics via quantum chemistry methods | 
 | 
 | 30 | 30 | P | 2 | 
| Facultative course IV: | 
 | 30 | 
 | 30 | P | 2 | 
| SEMESTER 3 | 105 | 60 | 255 | 420 | 1 | 30 | 
| SEMESTER 4 | ||||||
| subject | lecture | auditorium lasses | laboratory classes | TOTAL | E/P | ECTS | 
| 30 | 
 | 
 | 30 | P | 2 | |
| 
 | 
 | 190 | 190 | P | 10 | |
| 
 | 30 | 
 | 30 | P | 4 | |
| Monographic lecture*: | 30 | 
 | 
 | 30 | P | 3 | 
| Facultative course V: | 
 | 
 | 30 | 30 | P | 2 | 
| Facultative course VI: | 
 | 30 | 
 | 30 | P | 2 | 
| MSc exam | E | 7 | ||||
| SEMESTER 4 | 60 | 60 | 220 | 340 | 1 | 30 | 
| YEAR II | 165 | 120 | 475 | 760 | 2 | 60 | 
ATTENTION: Colours refer to two blocks of methods: (i) physics-based methods and (ii) data-based (chemoinformatics) methods
E – exam
P – pass with note
PWN – pass without note
*classes conducted at the Department, where the student is doing his master’s thesis
Second-cycle studies end with master’s examination and obtaining the professional title of master’s degree.