Operationalising Data Science & AI

What can help you unlock the potential of finance with data? 
In the dynamic, data-driven landscape of today, how do we harness the transformative potential of Data Science and AI (DSAI)?

Diving into this course will help you understand how to successfully deploy and scale DSAI projects in your organisation, empowering you to fuel innovation and make decisions that truly resonate in our data-centric world.
The data science stats in 2022 estimate that 149 zettabytes of data will be copied, captured, and curated by 2024.
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Online Course


30 mins

Video duration




On Completion

Badge of completion

With this online course, you will:
  • Understand the foundational concepts of Data Science & Artificial Intelligence (DSAI) in business decision-making processes
  • Recognize the key components essential for operationalising AI in a business context
  • Gain insights into the practical aspects of deploying and integrating DSAI into business operations
  • Develop strategies for effectively implementing DSAI to enhance efficiency and innovation
  • Evaluate the potential benefits and challenges of integrating DSAI into existing processes

Data Science

Artificial Intelligence

Machine Learning

Business decision-making

DSAI integration

Course Lessons

Chapter 1: Brief Intro to Data Science and AI (DSAI)

This is the foundation of any DSAI project. Data can come from various sources such as financial statements, transaction logs, social media, or economic indicators. Proper collection, cleaning, and preprocessing of data are crucial steps to ensure the accuracy and reliability of any subsequent analysis or modelling.

Chapter 2: What are the Pieces of the DSAI Puzzle?

Understanding the process of modelling and how it plays a vital role in gaining confidence that the proposed solutions work.

Chapter 3: How to Operationalise DSAI?

Clearly defined objectives guide the entire data science process. Knowing the "why" behind a project helps in making crucial decisions like data sourcing, model selection, and evaluation criteria.

Meet your instructor - Dr. David R. Hardoon

Chief data and AI Officer, Union Bank of the Philippines

Executive with 22 years of Data & AI experience in roles in senior management, start-up, advisory, research, academia, investment and board, David led the development of the AI strategy for the Monetary Authority of Singapore's financial sector as well as driving efforts in promoting open cross-border data flows. He has pioneered the regulator and central bank adoption of data science as well as the establishment of the Fairness, Ethics, Accountability and Transparency (FEAT) principles, first-of-a-kind guidelines for adopting Artificial Intelligence in the financial industry.

David has extensive exposure and experience in both industry and academia and he has consistently applied advanced technology with an analytical mindset to shape and deliver innovation.