Lectures

Date	Lecture	Topic	Slides	Code
19.02.2025	1	Basic data structures - arrays, sets, dictionaries, algorithmic complexity motivation	Lecture 1	Notebook 1
26.02.2025	2	2D arrays (matrices), array processing (search, cumulative sum)	Lecture 2	Notebook 2
05.03.2025	3	Strings, text processing, string edit distance, files	Lecture 3	Notebook 3
12.03.2025	4	Numpy arrays	Lecture 4	Notebook 4
19.03.2025	5	Array processing II (sliding window, sorting, convolution, sparse matrices)	Lecture 5	Notebook 5
26.03.2025	6	ADT - trees, stacks, queues	Lecture 6 Example	Notebook 6 Example
02.04.2025	7	Refresher lecture (preparation for midterm)		Midterm examples
09.04.2025	8	Trees and recursion I	Lecture 7	Notebook 7
16.04.2025	9	Trees and recursion II	Lecture 8	Notebook 8
23.04.2025	10	Scientific Python libraries - data loading and processing	Lecture 9	Notebook 9
30.04.2025	11	Scientific Python libraries - visualization	Lecture 10	Notebook 10
07.05.2025	12	Run time estimation, profiling, asymptotic complexity	Lecture 11	Notebook 11
14.05.2025	13	Rector's day
21.05.2025	14	Reserve, preparation for exam

Supplementary material for lectures

| NumPy (& string + list) cheatsheet

The supplementary materials (interactive Jupyter notebooks) for the lectures are located here:

pge_lectures@FEL Gitlab

Download the repository and read the instruction for installation in the `README.md` file. It is assumed that you already have Python installed, ideally (but not necessarily) with some Python environment management. For example, Conda or Mamba.

Slides and supplementary materials to lectures will be added progressively during the semester, as this course is going through changes.