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Machine learning is a topic which is leading the trend in the transformation of organisations from digitisation to data driven. This course aims to expose the learner to the code underpinnings of constructing and assessing a subset of the machine learning tasks, namely the classification, time series and clustering/feature extraction tasks. The objective is to target commonly encountered tasks in the space of financial data analysis. Participants will be able to gain familiarity in such tasks and have a deeper understanding of tackling them.
This course should be attended by those are who are keen to explore the challenges in dealing with finance and machine learning. Applicable to students, working professionals and PMETs.
This course expects that learners come in a basic understanding of python, from there we will build upon their understanding and teach from a data point of view.
A Laptop or desktop is required to access this course.
This course is led by experienced trainer who has extensive experience in technology services across global firms and carries a wide-ranging experience in various machine learning modelling, core programming and software development, and digital transformation initiatives. The trainer is adept in engaging with global stakeholders to deliver time-critical, cross-functional projects. With in-depth knowledge and experience in various industries, from technical solution providers to financial services, trainer brings a wealth of corporate knowledge which reinforces skills to impact and connect during training engagements with the audience.