Graduate university study programme Mathematics, specialisation in Statistics and Computer Science - Prirodoslovno-matematički fakultet Sveučilišta u Splitu

The programme for this specialisation is based on a syllabus for the acquisition of competences in computer science, an area of mathematics relevant to computer science as well as mathematical and applied statistics. The expectation is that students who complete this specialisation will be able to apply mathematical methods in solving specific tasks, master abstract approaches to solving problems in the area of computer science and software engineering, as well as solve problems relating to probability and statistical modelling, artificial intelligence and data analysis. After completing this specialisation, holders of the master’s degree will be able to gain employment in IT companies, the financial sector (as analysts, actuaries, …), in companies researching and developing artificial intelligence, in higher education institutions, and generally in jobs seeking abilities in mathematic modelling, programming and analytical thinking, application of advanced probability and computer models.

I semester

LIST OF COURSES
Year of study: 1.
semester: 1.
STATUS	CODE	COURSE	HORS IN THE SEMESTER				ECTS
STATUS	CODE	COURSE	P	S	V	T	ECTS
Mandatory	PMM913	Measure and integral	30		30		6
	PMM911	STATISTICS IN COMPUTER SCIENCE	30		30		5
	PMM922	Optimization	30	15			5
	PMID40	Parallel Programming	30		30		5
	PMM306	FINANCIAL MATHEMATICS	30		30		5
	Total mandatory		195	15	150		26
Elective	Group of Electuve course Mathematics
	PMM912	Metric spaces	45	15			6
	PMM204	Mathematical Theory of Computation	45		15		5
	Group of Electuve course Informatics
	PMIH10	Databases	30		30		5
	PMIH25	Introduction to Data science	30		30		5
	PMIH21	Machine Learning	30		30		5

II semester

LIST OF COURSES
Year of study: 1.
semester: 2.
STATUS	CODE	COURSE	HORS IN THE SEMESTER				ECTS
STATUS	CODE	COURSE	P	S	V	T	ECTS
Mandatory	PMID45	Programming paradigms	30		30		5
	PMIH20	Data minning	30		30		5
	PMIE20	Algorithms in Bioinformatics	30		30		5
	PMM228	Probability I	30		30		6
	PMM210	Numerical linear algebra	30		30		5
	Total mandatory		195	15	150		26
Elective	Elective courses of Mathematics
	PMM806	Graph theory	30		30		5
	PMM215	Normed spaces	45	15			6
	PMM129	Computability	30		15		5
	PMM118	Numerical analysis	30		30		5
	Elective courses of Computer Science
	PMID60	Compilers	30		30		5
	PMIH12	Distributed and non-relational databases	30		30		5
	THE STUDENTS SELECT AT LEAST 10 ECTS OR TWO COURSES FROM THE GROUP OF ELECTIVE COURSES FOR THE 1ST AND 2ND SEMESTER COMBINED.

III semester

LIST OF COURSES
Year of study: 2.
semester: 3.
STATUS	CODE	COURSE	HORS IN THE SEMESTER				ECTS
STATUS	CODE	COURSE	P	S	V	T	ECTS
Mandatory	PMM920	Complexity of algorithms	30		30		6
	PMII15	Deep Learning	30		30		5
	PMM127	Game Theory	30		30		5
	PMM501	Applied spatial statistics	30		30		4
	PMM205	Cryptography	30	15	15		5
	PMM219	STOCHASTIC PROCESSES	30		30		6
	Total mandatory		195	15	150		31

IV semester

LIST OF COURSES
Year of study: 2.
semester: 4.
STATUS	CODE	COURSE	HORS IN THE SEMESTER				ECTS
STATUS	CODE	COURSE	P	S	V	T	ECTS
Mandatory	PMM991	Diploma thesis		30			22
Mandatory	Total mandatory		60	30	60		22
Elective	Moduls
	PMM502	Complex networks analysis	30		30		5
	PMM503	Finance lab	30		30		5
	PMM504	Statistics in biomedicine	30		30		5
	PMM710	Mathematics in Action					5
	The students select at least 5 ECTS or one course from the group of elective courses MODULes for the 4^th SEMESTeR.

CONDITIONS OF ENROLLMENT AND POTENTIAL DIFFERENTIAL COURSES:	ANY UNDERGRADUATE STUDY OF MATHEMATICS OR MATHEMATICS AND OTHER FIELD WITH AT LEAST 115 ECTS IN MATHEMATICAL COURSES AND AT LEAST 39 ECTS IN INFORMATICS / COMPUTER SCIENCE / COMPUTER ENGINEERING COURSES. TOTAL DIFFERENTIAL COURSES CAN NOT EXCEED 30 ECTS.