COURSE DETAIL
COURSE DETAIL
COURSE DETAIL
The purpose of the course is to introduce non-Computer Science students to probabilistic data modelling and the most common techniques from statistical machine learning and data mining. It provides a working knowledge of basic data modelling and data analysis using fundamental machine learning techniques. Topics include: foundations of statistical learning, probability theory; classification methods, such as Linear models, K-Nearest Neighbor; regression methods, such as Linear regression; Bayesian Statistics; clustering; dimensionality reduction and visualization techniques such as principal component analysis (PCA).
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This course provides a study of requirements engineering, conceptual modeling with UML, and architectural modeling with UML. It discusses the process of analysis, design, and troubleshooting of applications and systems, ensuring their reliability, security, and quality in accordance with ethical principles and existing legislation and regulation.
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This course offers an introduction to databases. Topics include: the entity relationship model; the relational database model; relational algebra; structured query language (SQL); procedural languages for SQL; triggers; transactions and concurrency control.
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This course focuses on the Google search engine and its online advertising platform Google Ads. It offers a study of how search engines work-- page indexing and ordering of results-- and the composition of search engine results pages.
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COURSE DETAIL
The course focuses on Big Data Aggregation for Bitcoin transaction analytics, including: Confirmed transactions on Blockchain; confirmed and unconfirmed transactions and associated data not included in Blockchain; data from digital currency exchanges, wallets, payment processors and miners; user data (payments, demographics etc.); illegal activities and payments; transaction analytics. The section on comprehensive database for credit metrics and fraud detection covers machine learning analytics for real-time transaction tracking and credit scoring; early warning system against fraudulent activities and hacking; identity verification and classification of persons or companies involved in a transaction.
COURSE DETAIL
COURSE DETAIL
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