Digital chemistry
Digital chemistry
CHEMISTRY
|
Course of education |
2025 – 2027 |
|
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 |
P |
3 |
|
Quantum chemistry in practice – lecture |
30 |
|
|
30 |
E |
3 |
|
Quantum chemistry in practice – laboratory classes |
|
|
45 |
45 |
P |
3 |
|
Exploratory analysis of multidimensional chemical space – lecture |
30 |
|
|
30 |
E |
3 |
|
Exploratory analysis of multidimensional chemical space – laboratory classes |
|
|
45 |
45 |
P |
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 |
P |
3 |
|
Molecular mechanics & dynamics, coarse-grain modeling – lecture |
30 |
|
|
30 |
E |
3 |
|
Molecular mechanics & dynamics, coarse-grain modeling – laboratory classes |
|
|
45 |
45 |
P |
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 |
P |
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 |
|
|
15 |
|
|
15 |
P |
1 |
|
|
|
|
30 |
30 |
P |
2 |
|
|
|
|
190 |
190 |
P |
10 |
|
|
MSc seminar* |
|
30 |
|
30 |
P |
4 |
|
Monographic lecture*: |
30 |
|
|
30 |
P |
3 |
|
Facultative course V: |
|
|
30 |
30 |
P |
2 |
|
Facultative coyrse VI: |
|
30 |
|
30 |
P |
2 |
|
Elective subjects: |
60 |
60 |
P |
4 |
||
|
Click, think, discover: online tools and AI in science (lecture) Click, think, discover: online tools and AI in science (laboratory classes) |
8 |
|
22 |
8 22 |
P P |
1 3 |
|
Fundamentals of molecular diagnostics (lecture + audytorium classes) |
15 |
15 |
|
30 |
P |
4 |
|
30 |
|
|
30 |
P |
4 |
|
|
Radiochemical methods and radiometric techniques for environment (lecture) |
30 |
|
|
30 |
P |
4 |
|
Solid-phase synthesis in peptide-based drug design and production (lecture) |
30 |
|
|
30 |
P |
4 |
|
What is pharmacology? (lecture) |
30 |
|
|
30 |
P |
4 |
|
MSc exam |
E |
|
||||
|
SEMESTER 4 |
135 |
60 |
250 |
445 |
1 |
30 |
|
YEAR II |
240 |
120 |
505 |
865 |
2 |
60 |
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.