Digital chemistry

Course of education

2026 – 2028

Specialisation

Digital Chemistry

Type of study

Second-cycle studies / Master’s study

Mode of study

Full-time studies

Study profile

academic

Subject card search engine

                                                                                 SEMESTER 1                                                                                  2026/2027

subject

lecture

auditorium classes

laboratory classes

TOTAL

E/P

ECTS

Education health and safety (e-learning; extended course)

5

5

PWN

0

AI in academic education

15

15

PWN

0

Repetitory in mathematics

30

30

P

3

Repetitory in general and inorganic chemistry

30

30

P

3

Repetitory in organic chemistry and biochemistry

30

30

P

3

Introduction to digital chemistry

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

140

135

360

3

30

                                                                                 SEMESTER 2                                                                                  2026/2027

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*:

- Statistical mechanics in chemistry

- Molecular descriptors

30

30

P

3

Graduate laboratory*

180

180

P

12

Facultative course I:

- Parallel programing in Python

- Data bases & big data

30

30

P

2

Facultative course II:

- Microcontroler-based chemical diagnosis

- Omics analysis in chemoinformatics

30

30

P

2

SEMESTER 2

75

30

300

405

2

30

YEAR I

160

170

435

765

5

60

                                                                                 SEMESTER 3                                                                                  2027/2028

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

Interpersonal communication

15

15

P

1

The activities of the company in contemporary environment

30

30

P

2

MSc laboratory course*

180

180

P

10

MSc seminar

30

30

P

4

Monographic lecture*:

- Modern quantum chemistry in use

- Machine learning algorithms for small datasets

30

30

P

3

Facultative course III:

- Insights into reaction mechanisms and kinetics via quantum chemistry methods

- QSAR in toxicology

30

30

P

2

Facultative course IV:

- Statistical mechanics of biological macromolecules

- Advanced nanoiformatics

30

30

P

2

SEMESTER 3

105

60

255

420

1

30

                                                                                 SEMESTER 4                                                        2027/2028

subject

lecture

auditorium lasses

laboratory classes

TOTAL

E/P

ECTS

Economic activity law

30

30

P

2

Introduction to statistics for life sciences

15

15

P

1

30

30

P

2

MSc laboratory course*

190

190

P

10

MSc seminar*

30

30

P

4

Monographic lecture*:

- Electronic structure of molecular anions

- Computational nanomedicine and nanotoxicology

30

30

P

3

Facultative course V:

- Numerical methods with algorythms for physical sciences

- Computationally added drug design

30

30

P

2

Facultative course VI:

- Chemical bonding via quantum chemistry tools

- Computational methods for designing advanced materials

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

Introduction to computational quantum chemistry (lecture)

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