Introduction to Data Analytics for ESG Application

Course Description

In the 21st Century, Data analytics in Sustainability, Environmental, Social and Governance (ESG) and Green Finance have become the hottest topics in global economic growth. To reduce climate-related risks and supporting the transition to a low carbon and sustainable world are our most significant global challenges. Talents and professionals in these areas are in high demand across the world now. In view of these, this course aims to provide an overview study and career enhancement opportunities for professionals in understanding the data analytics spectrum of Sustainability and Green Finance.

Course Overview

This session will enhance your understanding of the application of data analytics in the areas of:
1. Green Finance, Sustainability, and ESG
2. Sustainability Reporting
3. Compliance, Regulations, and Green Investing

You should take this class if

You are...

  • Exploring career fields opportunities in data science
  • An aspiring sustainability professional
  • Executives and staff who will deal with ESG, Compliance, Regulations and Green Investing.
  • Legal staff, Compliance Officers, Securities Staff, Accountants, Financial Analysts, Fund Managers, and Investors

Your Instructor

Patrick Tsoi is an Experienced Trainer, Educator, and Chief Data Scientist with a demonstrated history of working in the talent training and staff recruiting industry. He is skilled in Hands-on Data Science Training, Learning Management, Instructional Design, Professional Services, and Programming.

His work includes complex projects applying data science, and software development to different aspects of value chains as well as participating with research teams, in fields such as Finance, Data Science, Quantitative Analysis and Talent Management. He has extensive experience in designing and building big data solutions and enterprise applications.

Difficulty Level: Beginner
Jam Date: Jul 31, 2021
Start Time (GMT + 8 hours): 1130
Jam Length (in hours) : 1.5
Learners Per Class : 15