1. SylabUZ
2. Wydział Matematyki, Informatyki i Ekonometrii
3. semestr letni 2023/2024
4. Data Engineering - drugiego stopnia z tyt. magistra
5. Methods and Tools for Data Processing

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Methods and Tools for Data Processing - opis przedmiotu

Cel przedmiotu

The aim of the course is to familiarize the student with the application of data processing methods and tools using the R program. After completing this course, the student should be prepared to use independently the studied methods and tools to solve practical problems specific to the field of data analysis.

Wymagania wstępne

Zapisz zmiany

Fundamentals of programming.

Zakres tematyczny

Lecture/Laboratory:

1. Data preprocessing.

• Data cleaning.
• Handling missing data.
• Improving wrong data.
• Numerical and categorical variables.
• Time series.

2. Data presentation and visualization methods.
3. Regression modeling. Linear and logistic regression.
4. Selected association rules and data clustering methods.
5. Examples of applications of data processing methods and tools.

Metody kształcenia

Lecture: traditional and problem-based. 
Laboratory: solving data mining problems using R program. Discussion.

Efekty uczenia się i metody weryfikacji osiągania efektów uczenia się

Opis efektu	Symbole efektów	Metody weryfikacji	Forma zajęć

Warunki zaliczenia

Laboratory evaluation is based on tests (80%) with tasks of varying difficulty, allowing to assess whether the student has achieved the learning outcomes to a minimum degree, and activity in class (20%). The lecture ends with an exam in the form of a test.

The final course evaluation consists of the grade from the laboratory (70%) and the grade from the lecture (30%).

The condition for passing the course is positive grades from the laboratory and the exam.

Literatura podstawowa

1. D.T. Larose, Data Mining Methods and Models, Wiley, 2006.
2. M. Bramer, Principles of Data Mining, Springer, 2007.
3. C.C. Aggarwal, Data Mining, Springer, 2017.

Literatura uzupełniająca

1. D.T. Larose, Discovering Knowledge in Data, Wiley, 2014.

Uwagi

Zmodyfikowane przez dr Maciej Niedziela (ostatnia modyfikacja: 11-04-2024 16:04)