Chemometrics

COURSE CURRICULUM 

1.

Course title

CHEMOMETRICS

2.

Code

HM-556

3.

Study curriculum

All study programs in chemistry

4.

Organizer of the curriculum (institute, department)

Institute of Chemistry, Faculty of Natural Sciences and Mathematics

5.

Degree (BSc, MSc, PhD)

BSc

6.

Academic year/semester

III/V (applied chemistry)

IV/VII (analytical biochemistry, teaching chemistry)

7.

ECTS points

4

8.

Lecturer

Prof. Dr. Igor Kuzmanovski

9.

Prerequisites

Mathematical methods in chemistry (applied chemistry)
Statistical data processing in chemistry (analytical biochemistry)
Mathematical methods in chemistry or Statistical data processing in chemistry (teaching chemistry)

10.

Course objectives (competences):
Obtaining profound knowledge of chemical data analysis studied in previous courses (mathematical methods in chemistry or statistical data processing in chemistry).

11.

Course content:
–    Signal and time series processing (signal processing, time series processing);
–    Data preprocessing (centering, scaling, autoscaling);
–    Chemical data modeling (robust linear regression, partial least squares regression, characteristic vector regression, validation of chemometric methods, cross-validation, domain of applicability);
–    Methods for classification and shape recognition (factor-analytical methods, data grouping, discriminant analysis, k-nearest neighbors, graphic methods);
–    Methods of artificial intelligence (unidirectional multilayer artificial neural networks, self-organizing maps, counter-propagation artificial neural networks, phase logic, genetic algorithms, support vector machines).

12.

Teaching methods: lectures, problem solving

13.

Total available time

120

14.

Time distribution

2+1+0 hours weekly (lectures: 45 hours;
problem solving: 30 hours)

15.

Teaching methods distribution

15.1.

Teaching - lectures

30 hours

15.2.

Practicals (laboratory, problem solving), seminars, team work

15 hours

16.

Other activities

16.1.

Projects

25 hours

16.2.

Independent work

20 hours

16.3.

Homework

30 hours

17.

Grading methods

17.1.

Tests

70 points

17.2.

Seminars/projects (written/oral presentation)

15 points

17.3.

Activity

 15 points

18.

Grading scale (points/mark)

< 50 points

5 (five) (F)

51 to 60 points

6 (six) (E)

61 to 70 points

7 (seven) (D)

71 to 80 points

8 (eight) (C)

81 to 90 points

9 (nine) (B)

91 to 100 points

10 (ten) (A)

19.

Criteria for taking the final exam

Attendance at lectures and completed exercises

20.

Course language

Macedonian, English

21.

Teaching quality control

Anonymous surveys, questionnaires

22.

Literature

22.1.

Compulsory

No.

Author

Title

Publisher

Year

1.

I. Kuzmanovski

Chemometrics – application of mathematical and statistical methods in chemistry (reviewed unpublished textbook)

2.

M. Otto

Chemometrics: Statistics and Computer Application in Analytical Chemistry

Wiley-WCH, Weinheim

2007

3.

J.N. Miller, J.C. Miller

Statistics and Chemometrics for Analytical Chemistry

Prentice Hall, Harlow

2000

22.2.

Additional

No.

Author

Title

Publisher

Year

1.

P.C. Meier, R.E. Zünd,

Statistical Methods in Analytical Chemistry

Wiley, New York,

2000