Infopaket

Big Data Analysis in Geology

ВК 2.8.7

Вибіркова дисципліна для ОП

First

2023/2024

7 Semester

7

Know the Components of Decision Support Systems Know the Types and Sources of Geological Data Know the Methods for Preparing Data for Data Mining Know Data Mining Models Know Data Mining Methods Know Data Mining Tools Be able to Create Data Warehouses from Diverse Data Sources Be able to Prepare Data for Analysis in Data Mining Systems Be able to Perform Data Mining on Geological Data Using Analytical Systems Organize Information Presentation in Databases in a User-Friendly Format for Efficient Problem Solving Formulate Written Reports on Created Databases, Algorithms, and Commands, Illustrating Examples of Developed Software Tools Understand Personal Responsibility for Individual Contributions to a Shared Task

Distance form

1. Successful completion of at least one course in statistical data processing. 2. Knowledge of the fundamentals of general geology, geophysics, and geochemistry. 3. Proficiency in programming, working with spreadsheets, databases, and other data sources.

An introduction to the fundamentals of data mining, methods for working with big data, and the construction of specific database structures (data warehouses, data marts) is provided. The general paradigms of data science and their role in modern decision support and data analysis systems are studied. Learners acquire practical skills in the intelligent analysis of geological data.

1. Pal A., Pal S.K. *Pattern Recognition and Big Data*. World Scientific Publishing, 2017. – 862 p. 2. Plaksina T. *Modern Data Analytics. Applied AI and Machine Learning for the Oil and Gas Industry*, 2019 – 77 p. 3. Marchenko O.O., Rossada T.V. *Current Issues in Data Mining: A Study Guide*. — Kyiv, 2017. — 150 p. 4. Gruber M. *Understanding SQL*, 1993, 291 p. 5. V. Pasichnyk, V. Reznychenko *Database and Knowledge Organization*. – Kyiv: BHV, 2006. – 383 p. 6. D. Ladychuk, V. Pichura *Geo-Information Databases*. – Kherson: KSU, 2007. – 103 p. 7. *Data Mining: Laboratory Practicum*: Study Guide / O.Yu. Vynnychuk, I.S. Vynnychuk. – Chernivtsi: Chernivtsi National University, 2014. – 80 p.

Lectures, practical sessions, independent work

Assessment is carried out through a modular rating system and includes: completion of 2 semester-long practical projects (where students must demonstrate their grasp of acquired knowledge and solve assigned tasks using methods and tools specified by the instructor), completion of 10 independent practical tasks (where students must show the quality of their knowledge and solve assigned tasks without restrictions on tools and techniques used for problem-solving), and 2 written modular assessments. Final evaluation is conducted in the form of a written exam.

Ukrainian