The course consists of 13 lectures and 7 exercises. Below is a preliminary lecture plan with problems connected to each lecture.

Solution manual and lecture notes will be distributed on the course Moodle page.

This is a preliminary planing, and it might change along the course:

Cal week	Lecture	Topic	Part in book
13	L1 25/3	Information measures	3.1-3.2
	L2 27/3	Properties of information measures	3.2-3.3
	E1 28/3	(2.1-.2.4, 2.8-2.11), 3.3-3.10, 3.13-3.15
14	L3 1/1	Optimal source coding and Kraft inequality	4.1-4.2
	L4 3/1	Huffman coding	4.3
	E2 4/1	4.1-4.8, 4.11
15	L5 8/4	Information measures for processes	3.4
	L6 10/4	LZ codes	5.2
	E3 11/4	3.18-3.21, 5.3, 5.5-5.7
16	L7 15/4	AEP and its consequences	6.1-6.2
	E4 17/4	6.1-6.3
17-18	Eastern and Re-exam period
19	L8 6/5	Capacity for DMC	6.3-6.5
	L9 8/5	Channel coding	7.1-7.2
	E5 9/5	6.5-6.10, 6.12a, 7.1-7.3
20	L10 13/5	Information measures for continuous variables	8.1-8.2
	L11 15/5	Gaussian channel	9.1-9.3
	E6 16/5	8.1, 8.2, 8.5-8.10, 9.2-9.4
21	L12 20/5	Parallel Gaussian channels, OFDM and MIMO	9.2-9.3
	L13 22/5	Discrete input Gaussian channel	10.1-10.4
	E7 23/5	9.5-9.8, 9.10, 10.1-10.3, 10.5, 10.6, 10.8, (10.7)
23	Exam week (1-8 June)