(in Polish) Przedmioty kierunkowe dla Data Science (course group defined by Faculty of Economic Sciences)
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2024Z - Winter semester 2024/25 2024L - Summer semester 2024/25 2025Z - Winter semester 2025/26 2025L - Summer semester 2025/26 (there could be semester, trimester or one-year classes) |
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| 2400-ZEWW846 |
 
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Classes
Winter semester 2024/25
Groups
Brief description
(in Polish) Kurs przygotowany przez Google prowadzony jest w pełni online za pośrednictwem platformy QWIKLABS. Kurs składa się z 3 obowiązkowych modułów i 4 dodatkowych modułów, których ukończenie nie jest konieczne do uzyskania zaliczenia. W każdym module dostępne są materiały wideo, interaktywne ćwiczenia oraz quiz sprawdzający wiedzę. W trakcie kursu studentów wspiera wykładowca z UW oraz dział techniczny Google. Szacowany nakład pracy potrzebny do ukończenia obowiązkowych modułów to ok. 40 godzin. Kurs przeznaczony jest dla osób, które ukończyły kurs From Data to Insights będący wprowadzeniem do narzędzi Google Cloud Platform. |
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| 2400-ZEWW908 | n/a |
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Classes
Summer semester 2024/25
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Brief description
As part of the course, students have the opportunity to learn the methods and process of the regulatory and non-regulatory credit risk models development, as well as the methods of their monitoring and validation. The subject matter focuses not only on statistical tools and their applications, but also describes the entire model life cycle in the bank. It is an academic course where knowledge is imparted by practitioners, therefore includes the latest and advanced practices applied in banks. During the course examples would be presented in R and Python. |
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| 2400-ZEWW947 | n/a |
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Classes
Summer semester 2024/25
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Brief description
No brief description found, go to course home page to get more information.
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| 2400-ZEWW939 |
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Classes
Winter semester 2024/25
Groups
Brief description
No brief description found, go to course home page to get more information.
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| 2400-ZEWW829 | n/a | n/a | n/a |
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Classes
Summer semester 2025/26
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Brief description
(in Polish) Metody bajesowskie są coraz częściej stosowane we wszystkich dziedzinach ekonomii. Dotyczy to zarówno samej teorii ekonomii jak i ekonomii stosowanej (nie tylko ekonometrii). Metody uczenia maszynowego również z powodzeniem stosują koncepcję bajesowską. Kurs będzie składał się z 2-ch modułów. W pierwszej części zajęć dokonamy wprowadzenia do koncepcji bajesowskiej. Pokażemy na przykładzie zwykłej regresji liniowej jak przebiega typowe (analityczne) wnioskowanie bajesowskie. Omówimy również metody Markov Chain Monte Carlo (MCMC), które są powszechnie stosowane w bajesowskim modelowaniu szeregów czasowych. W drugim bloku zajęć będziemy stosować formułę Bayesa w celu estymacji modeli, które należą do kanonu nowoczesnej ekonometrii szeregów czasowych. Będziemy rozważać zarówno jednowymiarowe jak i wielowymiarowe modele. |
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| 2400-ZEWW906 |
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Classes
Winter semester 2024/25
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Brief description
No brief description found, go to course home page to get more information.
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| 2400-ZEWW752 | n/a |
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Classes
Summer semester 2024/25
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Brief description
The course gives both theoretical knowledge and practical skills to model a credit scorecard. During the course all necessary steps to develop a scorecard would be discussed and presented. Starting from data preparation (handling a missing data and outliers, derived variables preparation, data sampling), going through model estimation (i.e. logistic regression) and model quality assessment (discriminatory power, stability) and ending on optimal cut-off choice. During the course examples would be presented in R. |
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| 2400-ZEWW949 | n/a |
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Classes
Summer semester 2024/25
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Brief description
No brief description found, go to course home page to get more information.
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| 2400-ZEWW669 |
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Classes
Winter semester 2024/25
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Brief description
The course aims to familiarize participants with the creation, modification and management of databases using SQL language, which is the standard used in databases such as Oracle, Sybase, Informix, Microsoft SQL Server, Access, etc. Students will become acquainted with the theoretical and the practical issues of database creation, maintenance and management. Special attention will be paid to the SQL queries in databases such as MS SQL Server. CAUTION: This course is is equivalent to course: BAZY DANYCH – ZASTOSOWANIA JĘZYKA SQL. |
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| 2400-ZEWW952 | n/a |
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Classes
Summer semester 2024/25
Groups
Brief description
No brief description found, go to course home page to get more information.
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| 2400-ZEWW953 | n/a |
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Classes
Summer semester 2024/25
Groups
Brief description
No brief description found, go to course home page to get more information.
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| 2400-ZEWW827 | n/a |
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Classes
Summer semester 2024/25
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Brief description
The course is conducted online via an e-learning platform. The course consists of 4 modules and additional mini-projects/tasks. Each module includes video materials and a quiz to check your knowledge. During the course, students are supported by a lecturer from the University of Warsaw and Google technical department. The estimated workload needed to complete the course is approximately 40 hours. The course is intended for beginners without prior knowledge of Google Cloud tools. Knowledge of the basics of SQL is recommended. |
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| 2400-ZEWW715 | n/a |
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Classes
Summer semester 2024/25
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Brief description
The course will have the following content: • AML course overview and subject introduction (2h) • Terrorist financing prevention and sanctions (4h) • Money laundering and terrorists financing risk factors (8h) • Money laundering prevention in practise (10h) • AML legal framework (4h) • Final exam (2h). Top 30% students of the class rank obtain access to a fast-track recruitment process to Citi's AML department. |
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| 2400-ZEWW937 | n/a |
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Classes
Summer semester 2024/25
Groups
Brief description
No brief description found, go to course home page to get more information.
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| 2400-ZEWW936 | n/a |
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Classes
Summer semester 2024/25
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Brief description
The analysis of point and line patterns is a growing branch of spatial econometrics which becomes more popular in economic research. The aim of this class is to introduce students to methods analysing and modelling point and line patterns. We will operate in R software; prior knowledge is not required but will be welcomed. The classes have a practical character, the pass mark is based on the review of an article (selected by the teacher) and a project in groups of 2. |
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| 2400-ZEWW863 |
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Classes
Winter semester 2024/25
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Brief description
This course studies quantitative approaches for solving dynamic economic models. There is a heavy theoretical component: this course provides basic background in dynamic programming techniques (Bellman equation) frequently used in modern economics. We will also study economic theory related to consumption and savings decisions. There is also a heavy computational component: we will study numerical methods (value function iteration, endogenous grid, policy function iteration and similar) and learn to apply them in deterministic and stochastic settings. We will use Julia, a modern, open source, high productivity language primarily used in technical and scientific computing. No prior knowledge of Julia is needed. |
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| 2400-ZEWW905 | n/a |
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Classes
Summer semester 2024/25
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Brief description
No brief description found, go to course home page to get more information.
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| 2400-ZEWW929 |
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Classes
Winter semester 2024/25
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Brief description
No brief description found, go to course home page to get more information.
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| 2400-ZEWW951 | n/a |
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Classes
Summer semester 2024/25
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Brief description
No brief description found, go to course home page to get more information.
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| 2400-ZEWW780 | n/a |
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Classes
Summer semester 2024/25
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Brief description
No brief description found, go to course home page to get more information.
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| 2400-ZEWW882 | n/a |
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Classes
Summer semester 2024/25
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Brief description
The aim of this course is to present the process of collecting and processing data for the use of official statistics. The role of definitions, methods of obtaining and limitations of collected data will be discussed. We will also discuss the influence of the data used on the results and conclusions of economic analysis. |
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| 2400-ZEWW866 | n/a |
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Classes
Summer semester 2024/25
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Brief description
No brief description found, go to course home page to get more information.
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| 2400-ZEWW878 |
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Classes
Winter semester 2024/25
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Brief description
Brief description of the course (max 1.000 characters) The course aims to provide a comprehensive review of topic modelling algorithms, i.e. a set of machine learning tools destined for automatised grouping of texts with respect to thematic motifs present in those. The introductory part of the course shall involve discussion on all steps that need to be performed before modelling, specifically web scraping techniques and textual data preprocessing practices. Next, topic modelling algorithms are planned to be introduced, from the very basic approaches, through the most popular Latent Dirichlet Allocation (LDA), to a state-of-the-art BERTopic algorithm. Furthermore, ways to combine topic modelling with time series analysis and markov chains are planned to be covered in the course. |
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| 2400-ZEWW948 | n/a |
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Classes
Summer semester 2024/25
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Brief description
No brief description found, go to course home page to get more information.
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