Universitatea Babeş-Bolyai Cluj-Napoca
Facultatea de Matematică şi Informatică
Ciclul de studii: Masterat
Domeniul: Matematica
Programul de studii: Matematică Computaţională - în limba maghiară
Limba de predare: Engleză

SYLLABUS

I. General data
Code	Subject	
MIG1001	Stochastic Modeling of Data	

Semester	Hours: C+S+L	Category	Status	
3	2+1+1	speciality	compulsory	

II. Full status faculty members
Name and	Scientific	Didactic	Chair	Type of activity	
surname	title	title		C	S	L	
CSATO Lehel	Ph.D.	Assoc.Prof.	Programming  Languages and Methods	*			

Associated faculty members
Name and	Scientific	Institution	Type of	Type of activity	
surname	title		position	C	S	L	

III. Course objectives

IV. Course contents

V. Bibliography
[1]. Russell S, Norvig P. (2003) Artificial Intelligence: A Modern Approach (Second Edition), Prentice Hall.
[2]. Mitchell T (1997) Machine Learning, McGraw Hill.
[3]. Bernardo J.M, Smith A.F.M (2000) Bayesian Theory, John Wiley & Sons.
[4]. MacKay D.J.C (2003) Information Theory, Inference and Learning Algorithms, Cambridge University Press, HTTP: http://wol.ra.phy.cam.ac.uk/mackay/itila/book.html.
[5]. Rasmussen C.E, Williams C.K.I (2006) Gaussian Processes for Machine Learning, The MIT Press.
[6]. Rabiner L.R, Juang, B.H (1986) An introduction to Hidden Markov models, IEEE ASSP Magazine, pp: 4-15.
[7]. Durbin R, Eddy S.R, Krogh A, Mitchison G (1999) Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge University Press.
[8]. Hyvärinen A, Karhunen J, Oja E (2001) Independent Component Analysis, Wiley-Interscience.
[9]. Barto A. (2002): Statistical Pattern Recognition, John Wiley & Sons.

VI. Thematic of didactic activities per weeks

VII. Didactic methods used

VIII. Assessment

IX. Additional references

	Dean,							Chair head,

	Date,							Course responsible,
								Assoc.Prof. CSATO Lehel, Ph.D.