Major courses for AAB - masters (grupa przedmiotów zdefiniowana przez Szkoła Główna Handlowa w Warszawie)
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Legenda
Jeśli przedmiot jest prowadzony w danym cyklu dydaktycznym, to w odpowiedniej komórce pojawi się koszyk rejestracyjny. Ikona koszyka zależy od tego, czy możesz się rejestrować na dany przedmiot.
- nie jesteś zalogowany 
- aktualnie nie możesz się rejestrować 
- możesz się zarejestrować 
- możesz się wyrejestrować (lub wycofać prośbę) 
- złożyłeś prośbę o zarejestrowanie (i nie możesz jej już wycofać) 
- jesteś pomyślnie zarejestrowany (i nie możesz się wyrejestrować)
Kliknij na ikonę "i" przy koszyku, aby uzyskać dodatkowe informacje.
20201 - Semestr zimowy 2020/21 20202 - Semestr letni 2020/21 20211 - Semestr zimowy 2021/22 20212 - Semestr letni 2021/22 20221 - Semestr zimowy 2022/23 20222 - Semestr letni 2022/23 (zajęcia mogą być semestralne, trymestralne lub roczne) |
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| 226161-D |
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Zajęcia przedmiotu
Semestr zimowy 2020/21
Grupy przedmiotu
Skrócony opis
Advanced analytics. Predictive modeling. Data imputation. Advanced regression techniques. Client Life Time Value. |
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| 222801-D |
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Zajęcia przedmiotu
Semestr zimowy 2020/21
Grupy przedmiotu
Skrócony opis
Global search vs. local search. Hard optimization (unimodal vs. multimodal search, continuous vs. discrete optimization). Simulated annealing algorithm, Tabu search method, Genetic algorithm, Differential evolution, Nelder-Mead method, Particle swarm optimization, Ant colony optimization, Iterated Local Search, Variable Neighborhood Search, Penalty method, GRG method, Augmented Lagrangean method, Fundamentals of complexity theory. Implementation of selected methods in GNU R. |
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| 220521-D |
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brak | brak |
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Zajęcia przedmiotu
Semestr zimowy 2021/22
Grupy przedmiotu
- (od 2023-10-01) Elective courses for QEM - masters
Skrócony opis
The course introduces the R programming language. The first lab discusses installing and configuring R and selected editors. The next block of labs introduces basic data structures: vectors and lists, and data structures based on them: matrices, and data frames. The last block of labs introduces basic programming techniques, including conditional execution, looping and mapping, and functions. Some additional packages are also described. |
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| 223091-D |
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Zajęcia przedmiotu
Semestr zimowy 2020/21
Grupy przedmiotu
- (od 2023-10-01) Elective courses for QEM - masters
Skrócony opis
Within the subject the following topics will be discussed: technological elements of Big Data, data types, Big Data analytics, data streams processing, big data applications, data privacy and ethical issues. |
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| 224391-D |
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Zajęcia przedmiotu
Semestr zimowy 2020/21
Grupy przedmiotu
- (od 2023-10-01) Elective courses for QEM - masters
Skrócony opis
Cloud computing. Infrastructure-as-a-service (IaaS). Platform-as-a-service (PaaS). Collection and data management in the cloud. Relational databases and data warehousing in the cloud. NoSQL databases. Data analytic in the cloud . BigData - Hadoop and Spark int the cloud. Numerical and scientific computing in the cloud - grid computing. Economic fundamentals of cloud computing. Optimizing cloud computing costs. Cloud security. |
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| 220311-D |
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brak | brak | brak | brak |
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Zajęcia przedmiotu
Semestr zimowy 2022/23
Grupy przedmiotu
Skrócony opis
The combination of statistics (descriptive and logistic regression), AI/ML (Artificial Intelligence and Machine Learning: elements of decision trees, XGBoosting, random forests, deep learning and variable selection heuristics) with programming in SAS and OpenSource is presented. During the course, software in SAS and OpenSource for building predictive models and simulating the credit approval process is improved and modified. Each class is usually a presentation of a program and algorithm along with a business interpretation. |
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| 220551-D |
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brak | brak | brak | brak |
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Zajęcia przedmiotu
Semestr zimowy 2022/23
Grupy przedmiotu
Skrócony opis
1. Cyberspace and digital economy 2. Introduction to information security 3. Cybersecurity and risk management 4. Attack vectors according to the MITRE ATT&CK framework 5. Case studies 6. The secure usage of digital services 7. The law in cybersecurity 8. The global digital companies 9. InfoOps in cyberspace 10. Hacking Artificial Intelligence 11. Ethical issues 12. Future trends in cybersecurity |
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| 223121-D |
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Zajęcia przedmiotu
Semestr zimowy 2020/21
Grupy przedmiotu
- (od 2023-10-01) Elective courses for QEM - masters
Skrócony opis
Classes are focused on teaching students advanced data mining and text mining techniques, including advanced methods of big data analysis. As a result of dynamic development of this interdisciplinary research a lot of effective algorithms were developed allowing automatically discovery of knowledge from databases, including unstructured data available in internet. This knowledge may be used in decision processes in business (including enterprises), science and technology. |
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| 223061-D |
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Zajęcia przedmiotu
Semestr zimowy 2020/21
Grupy przedmiotu
Skrócony opis
Principles of relational database building. Object (abstract) data types which make possible to create internally composed structures as array or table. Basic types of queries - overview. Advanced queries which allow to work in corporate environment with big volume databases, many different structures, highly diversified users information need. Aggregate functions, analytical functions, commands dedicated to datawarehouse systems. |
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| 223481-D |
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Zajęcia przedmiotu
Semestr zimowy 2020/21
Grupy przedmiotu
Skrócony opis
The aim of the course is to provide student with a knowledge about logistic regression analysis and contingency tables analysis. Students are able to learn about the history and philosophy of binary, oridinal and multinominal logistic models, procedures of estimation and evaluation of the logistic and loglinear models, as well as experience practical application of the presented methods to the social science, medicine and economic research. The main statistical software utilized will be SAS with examples in R & Python. |
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| 220541-D |
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brak | brak |
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Zajęcia przedmiotu
Semestr zimowy 2021/22
Grupy przedmiotu
Skrócony opis
See the semester plan |
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| 223101-D |
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Zajęcia przedmiotu
Semestr zimowy 2020/21
Grupy przedmiotu
- (od 2023-10-01) Elective courses for QEM - masters
Skrócony opis
Within the subject the following topics will be discussed: methods of data visualisation, visualisation tools, visual data exploration, visualisation of spatial data, building interactive visualisations. Subject contains lectures and practical exercises concerning visual data exploration and building different kind of visualisations. |
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| 222891-D |
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Zajęcia przedmiotu
Semestr zimowy 2020/21
Grupy przedmiotu
- (od 2023-10-01) Elective courses for QEM - masters
Skrócony opis
1. Modelling, learning and prediction in batch mode (offline learning) and incremental (online learning) modes. Problems of incremental machine learning. 2. Data processing models in Big Data. From flat files to Data Lake. Real-time data myth and facts 3. NRT systems (near real-time systems), data acquisition, streaming and analytics. 4. Algorithms for estimating model parameters in incremental mode. Stochastic Gradient Descent 5. Modern streaming application architectures 6. Preparation of the microservice with the ML model for prediction use. 7. Processing structured and unstructured data in Python. Function and Object-oriented connection to RDB and NoSQL 8. Aggregations and reporting in NoSQL databases (MongoDB) 9. Basics of object-oriented programming in Python in linear and logistic regression, neural network analysis using the sklearn, TensorFlow and Keras. 10. IT streaming architecture. Apache Spark and Jupyter notebook environment using docker tool. Analysis of data |
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| 223491-D |
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Zajęcia przedmiotu
Semestr zimowy 2020/21
Grupy przedmiotu
- (od 2023-10-01) Elective courses for QEM - masters
Skrócony opis
Getting to know statistical algorithms of predictive model building used in decision making support. Practical aspects of model building: data collection and transformation, parameter estimation, prediction and decision making support based on models implemented in Julia, Python and R language. Model Evaluation measurements and visualization. |
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