Digital Chemistry

CHEMISTRY

Course of education	2023- 2025
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
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	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: - 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	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
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
*subject*	*lecture*	*auditorium lasses*	*laboratory classes*	*TOTAL*	*E/P*	*ECTS*
Economic activity law	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 agroithms 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
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.

Submitted on Saturday, 13. May 2023 - 23:23 by Andrzej Nowacki Changed on Sunday, 14. May 2023 - 20:08 by Andrzej Nowacki