Offered By: IBM
Secure analysis of credit card dataset
Learn to make the preliminary data analysis in security area based on credit clients card dataset with the helping frameworks and libraries.
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604 EnrolledAt a Glance
Learn to make the preliminary data analysis in security area based on credit clients card dataset with the helping frameworks and libraries.
Learning Objectives
- explore the credit card client’s dataset and to calculate the main statistical indicators.
- build different dependencies among existed attributes of dataset.
- visualize the data analysis results with various plot types.
Estimated Effort
1 hours
Level
Skills You Will Learn
Data Science
Language
Instructors
Sergii Kavun
Developer, DL/ML/DS
Data Science, Data Mining, Artificial Intelligence, Information Security and Intelligence Control, Economic Security Modelling, Machine Learning / Deep Learning Modelling (Optimization), Architecture Design. Experienced in the full set of aspects of the ML & DL lifecycle: concept (architecture design, PoC) & preparing datasets, training NN & hyperparameters optimization, deployment (MVP). Successfully managed projects and developers' teams. Focused on solving complex problems (issues) and their decomposition, and developing solutions from scratch to the SOTA level. 390+ (3 patents; 26 textbooks; 40+ monographs; 125+ manuscripts; 85+ conference publications). Memberships: WorkGroup 11.1, Information Security Management, International Federation for Information Processing, IFIP, 03.2019-; Association for Computing Machinery, ACM, 03.2019-; American Association for Science and Technology, AASCIT, 03.2014-.
Read moreYaroslav Vyklyuk
Full Professor, Doctor of Computer Science, PhD
Dr. Yaroslav Vyklyuk is a full professor at the Lviv Polytechnic National University, Department of Artificial Intelligence Systems. He is an author of over 210 scientific works, 10 monographs, and books, a member of the Editorial Board of 6 international scientific journals, member of the Academic Councils on protection Ph.D. and DrSc thesis in "Mathematical modeling and computational methods". Research Interests: Data Science, Applied System Analysis, Mathematical Modeling, and Decision Making of Complex Dynamic Systems (socio-economic, geographical, tourist, and crisis systems) using Artificial Intelligence Technology, DataMining, Big Data, Parallel Calculations, Statistics, Econometrics, Econophysics and other Advanced Mathematical Methods with implementation into information, WEB, and geographic information systems.
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