Data Analytics for Finance Professionals
Machine learning in finance sits at the intersection of a number of emergent and established disciplines, including pattern recognition, financial econometrics, statistical computing, probabilistic programming, and dynamic programming. With the trend towards increasing computational resources and larger datasets, machine learning has grown into a central computational engineering field, with an emphasis placed on plug-and-play algorithms made available through open-source machine learning toolkits.
Algorithm focused areas of finance, such as algorithmic trading, have been the primary adopters of this technology. But outside of engineering-based research groups and business activities, much of the field remains a mystery. This is where we can potentially add value. This professional short course should ideally bring the techniques of engineering and computer science to Finance’s practical use case.
ABOUT THE SPEAKER
Mr. Francis Adrian Viernes, CFA, MSF, CCREP
Head of Data Analytics, Chief Data Scientist of MEGAWORLD CORPORATION
Currently, the Assistant Vice President, Head of Data Analytics, MEGAWORLD CORPORATION, and the Chief Data and Tokenomics Officer, Board of Director, Likha Creatives Inc., Mr. Viernes is a leader in the burgeoning field of Data Analytics in the Philippines. Having earned his MSc in Finance from UP and his BA in Economics from Ateneo De Manila University, Mr. Viernes is also active as faculty in De La Salle University, University of Santo Tomas, and Southville International School affiliated with Foreign Universities.