This is the first PhD-level course on the design and the analysis of
efficient algorithms, with a strong emphasis on theoretical aspects. The
prerequisites are a very basic knowledge of graph theory and
computational complexity, as well as a good understanding of
undergraduate-level courses of algorithms, discrete mathematics, and
operation research.

It is not necessary to have already taken a graduate-level course on algorithms.

The goal of the course is to give a broad coverage of the main
techniques in algorithm design and analysis, so that the course can be
useful also for a researcher in a different field. To this purpose, the
computational problems tackled are among the most basic problems on
strings and graphs, such as pattern matching, vertex cover and max cut.

In fact, anyone that deals with one of the following questions will find the course interesting.

- How can I cope with problems that are provably hard to solve exactly (i.e. are NP-hard)?
- How can I exploit the massive availability of CPUs?
- How can I query efficiently massive texts?

### Exam

The exam will consists of some exercises that will be given during the course.

Collaboration is encouraged, but each student must write their own version of the solution.#### Lecture style

The lectures will be online at meet.google.com/yuu-giuj-movWhile the lectures will be recorded, I want to have highly interactive lectures, applying the*active learning*pedagogical technique. For this reason, watching videos is not an adequate substitute for actually attending lectures.All teaching material is at https://github.com/AlgoLab/advanced-algorithmsLink to the third lecture on text indexing (June, 4): https://meet.google.com/gib-gbvn-migUse this forum for anything that is related to the course.

**Lectures on Text Indexing**