Requirements and grading of the homeworks:

In order to pass the course 70% of practice sessions are obligatory to attend.
Each week after the lecture there is a homework assignment that gives maximum of 5 points (+ extra tasks with bonus points).
Homeworks should be submitted in pdf + script in programming language of your preference and uploaded here.
The deadline of the homeworks for all the groups is 23:59 on Sunday 10 days after the lecture, i.e if the lecture is on 12th of February, the deadline of the homework is 22nd of February.
NB! Homeworks submitted after the deadline will not be graded nor corrected.
Points for homeworks will be posted here.

Weekly homeworks:

HW 0 - Week of Feb 16.-20., TA-s will give a in-class tutorial on R. Please attend!

HW 1 (due Feb 22nd) Introduction (probability, R, business).

NB! The deadline for HW submissions is Sunday, Feb 22nd.
NB! Monday, Feb 23rd is officially a holiday at University (due Independence day on 24th). Monday group people would have to attend either the Wednesday or Friday groups. More info from TA-s.

HW 2 (due March 1st) Frequent itemsets, Apriori, FP-tree, R - arules

HW 3 (due March 8th) Association rules continued...

HW 4 (due March 15th) Association rule interestingness, elements of descriptive analysis.

HW 5 (due March 22nd) Descriptive analysis.

HW 6 (due March 29th) Descriptive analysis and visualisation

HW 7 (due April 5th) Visualisation, regression, clustering ...

HW 8 (due April 12th) Clustering ...

HW 9 (due April 19th) Clustering continued...

HW 10 (due April 26th) Clustering, Seriation, ...

HW 11 (due May 3rd) Classification - scores

HW 12 (due May 17th) Machine learning...