Facultative courses for 3-5th grade Computer Science (course group defined by Faculty of Mathematics, Informatics, and Mechanics)

Winter semester 2023/24

• Lab - 30 hours
• Lecture - 30 hours

Overview of the data processing pipeline; collection and storage of raw data; processing, cleaning, and storage of processed data; scaling tools for the data processing system.

Summer semester 2023/24

• Lab - 30 hours

Summer semester 2024/25

• Lab - 30 hours

No brief description found, go to course home page to get more information.

Summer semester 2024/25

• Classes - 30 hours
• Lecture - 30 hours

Complexity theory classifies problems according to their difficulty and explains why some problems are too hard to be solved by good algorithms. This lecture is a continuation of the “Computational complexity” course. We will discuss classic topics of complexity theory that did not fit into that course.

Summer semester 2023/24

• Lab - 30 hours
• Lecture - 30 hours

Summer semester 2024/25

• Lab - 30 hours
• Lecture - 30 hours

The lecture aims to present central issues in modern functional programming in languages such as Haskell, Coq, Idris, especially focusing on usung types for program specification and verification.

Summer semester 2023/24

• Lab - 30 hours
• Lecture - 30 hours

Summer semester 2024/25

• Lab - 30 hours
• Lecture - 30 hours

The course it is highly recommended for students who plan to attend Master Seminar on Distributed Systems, which is partly devoted to operating systems and in particular distributed operating systems. The course will have a form of lectures and labs.

We plan to view in detail the structure of a specific operating system. The chosen case study is Linux which is modern operating system, popular in the Faculty of Mathematics, Computer Science and Mechanics, University of Warsaw, often used as server platform, but also on desktops, mobiles, as embedded system. Source code of Linux is freely available which gives a unique opportunity to analyze in detail used algorithms, data structures, and also to run experiments and do research in the area of operating systems.

Winter semester 2024/25

• Classes - 30 hours
• Lecture - 30 hours

The lecture connects elements of structural graph theory, parameterised algorithms, and finite model theory. The main theme are algorithmic results called “algorithmic meta-theorems”, which express that entire families of computation problems can be solved efficiently on inputs enjoying specific structural properties. Typically we will consider graph problems for graphs of a particular form. For instance, every computational problem that can be expressed as a first-order sentence can be solved in linear time, on all planar graphs, or all graphs with maximum degree bounded by a fixed constant. This result can be extended to other graph classes (including nowhere dense graph classes, and monadically stable graph classes), and other logics.

Note: Course given in English

Winter semester 2023/24

• Classes - 30 hours
• Lecture - 30 hours

Winter semester 2024/25

• Classes - 30 hours
• Lecture - 30 hours

The lecture is addressed to students of mathematics as well as to students of computer science interested in theoretical or applied aspects of approximate reasoning. Issues and problems discussed in the lecture are considered by many famous mathematicians and computer scientists to be among central problems of the current century, as important as deciphering the genetic code was for the second half of the 20th century. We will discuss problems important for making progress in many projects, in particular, interdisciplinary projects, in which mathematicians and computer scientists work together with specialists from other areas such as neuroscience, bioinformatics, psychology, economy, or complex adaptive systems. Different theoretical and applied aspects of methods of concept approximation from experimental data and domain knowledge will be covered.

Winter semester 2023/24

• Classes - 30 hours
• Lecture - 30 hours

Winter semester 2024/25

• Classes - 30 hours
• Lecture - 30 hours

Auctions are a widely used mechanisms for resource exchange and allocation, that finds application in real world (e.g. internet auctions) as well as computational applications (e.g. resource allocation in multi-agent systems and eCommerce). Which auctions are best for the seller and which for the buyers? What is the impact of knowledge of others' valuations? How bad is collusion? Is it hard to determine the winner when bundles of several interdependent objects are being sold? Does it depend on the bidding language?

The aim of this course is to introduce and present the basic issues and problems of arising in auctions and to deepen their understanding via game theory and computational complexity theory.

Winter semester 2023/24

• Classes - 30 hours
• Lecture - 30 hours

Winter semester 2024/25

• Classes - 30 hours
• Lecture - 30 hours

The subject consolidates both theoretical and practical knowledge about machine learning and data mining methods in applications related to large, heterogeneous, distributed and dynamically growing data. We discuss problems concerning reliability and quality of data in tasks of teaching effective models for classification, prediction and related applications as well as maintaining the effectiveness of such models applied as components of larger IT systems. We refer to a wide range of practical sources and shapes of data, in particular machine-generated data. We cover a wide range of practical tasks in machine learning and data analysis, e.g. anomaly detection or recognition of similarities. Based on practical examples, we discuss the full life cycle of data and information in processing and analysis systems, including properly integrated solutions based on machine learning and data analysis.

Summer semester 2023/24

• Lab - 30 hours
• Lecture - 30 hours

(in Polish) Program obejmuje dwa obszary zastosowań informatyki będące obecnie w kręgu głównych zainteresowań biznesu z uwagi na oferowane lub spodziewane źródła przewagi konkurencyjnej: chmurę obliczeniową i uczenie maszynowe. Ujęcie zagadnień z zachowaniem podejścia, w którym środowiska chmurowe (głównie typu IaaS i PaaS) są przede wszystkim kontekstem wykonawczym pozwoli skupić się słuchaczom na rozwiązywaniu konkretnych problemów manifestując tym samym podejście pragmatyczne. Całości towarzyszy wspólna praca wraz z partnerem biznesowym nad projektem integrującym tematy z zakresu programu przedmiotu, którego wykonanie jest wymaganym elementem uzyskania oceny. Wybór konkretnych zagadnień wykładu zależy od scenariuszy przedstawionych przez partnera biznesowego, lecz będzie obejmować co najmniej modelowanie matematyczne, szeregi czasowe i techniki przetwarzania języka naturalnego (NLP).

Winter semester 2023/24

• Classes - 30 hours
• Lecture - 30 hours

Winter semester 2024/25

• Classes - 30 hours
• Lecture - 30 hours

Analysis of selected problems of computational geometry and methods which solve them (sweep line, divide and conquer, prune and search, duality etc.). Theory and applications.

Summer semester 2023/24

• Lab - 30 hours
• Lecture - 30 hours

This is an introduction to convex optimization, giving an overview of the landscape of convex optimization problems, and covering the most important convex optimization algorithms and lower bounds, as well as convex modelling techniques. The lab sessions cover convex modelling using modern software and implementation of selected convex optimization algorithms.

Summer semester 2023/24

• Classes - 30 hours
• Lecture - 30 hours

The course provides an introduction to modern cryptography, focusing on the CS foundations of the field. We present the most essential cryptographic techniques used today to secure digital communications. Particular emphasis is placed on formal security analysis and understanding its assumptions. The last few lectures are devoted to an introduction to more advanced aspects of cryptography. These topics will be deepened in the subject "Cryptography 2", to which the subject "Cryptography 1" is an introduction.

Summer semester 2023/24

• Lab - 30 hours
• Lecture - 30 hours

Summer semester 2024/25

• Lab - 30 hours
• Lecture - 30 hours

Presentation of the main issues in the field of data mining and the methods to resolve them. Discussion about the efficient implementation on large collections of data for basic problems, such as associative rules, data preparation, discretization of real value attributes, decision tree. Presentation of modern computation techniques such as parallel processing, evolutionary computation, using standard heuristic databases or specially constructed data structures.

Winter semester 2023/24

• Lab - 30 hours
• Lecture - 30 hours

Winter semester 2024/25

• Lab - 30 hours
• Lecture - 30 hours

The course takes an engineer’s perspective on building the complex set of systems and services that together provide the public cloud. The cloud infrastructure is a complex distributed system with unique requirements: high availability, massive scale and having deep software stacks. We plan to show how these requirements influence the key design decisions (communication, scalability, resource management, data management) and reliability engineering (monitoring, testing). The course will be delivered by Google engineers whose day-to-day work involves designing, building and maintaining cloud infrastructure.

In contrast to teaching specific cloud technologies, our goal is to rather show principles driving the design of large-scale distributed systems. We plan to illustrate these principles using specific systems developed by your lecturers.