Ricardo Sanchez-Matilla

Ricardo Sanchez-Matilla

Teaching

Senior Teacher Assistant - Data Mining

Data Mining, Queen Mary University of London, 2019

Data that has relevance for decision-making is accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations such as the Internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, and electronic patient records. Data mining is a rapidly growing field that is concerned with developing techniques to assist decision-makers to make intelligent use of these repositories. The field of data mining has evolved from the disciplines of statistics and artificial intelligence. This module will combine practical exploration of data mining techniques with a exploration of algorithms, including their limitations. Students taking this module should have an elementary understanding of probability concepts and some experience of programming.

Teacher Assistant - Data Analytics

Data Analytics, Queen Mary University of London, 2019

This module focuses on the range of approaches, methodologies, techniques and tools for data analysis, and the use of data analysis findings to inform decision-making in an industrial / business context. It exposes students to a range of industry-standard statistical and data analysis techniques and tools, and fosters awareness of the challenges associated with working with large datasets. The module also covers topics related to the legal, social, ethical and professional issues associated with data storage and analysis. Students will undertake practical work including empirical data analysis and summarisation / presentation of the results to a range of relevant stakeholders.

Teacher Assistant - Data Mining

Data Mining, Queen Mary University of London, 2018

Data that has relevance for decision-making is accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations such as the Internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, and electronic patient records. Data mining is a rapidly growing field that is concerned with developing techniques to assist decision-makers to make intelligent use of these repositories. The field of data mining has evolved from the disciplines of statistics and artificial intelligence. This module will combine practical exploration of data mining techniques with a exploration of algorithms, including their limitations. Students taking this module should have an elementary understanding of probability concepts and some experience of programming.