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CFTE

Generative AI for Climate Change in Financial Services

  • up to 6 weeks
  • Intermediate

This course equips professionals with the knowledge and skills to leverage generative AI technologies in their ESG strategies. Over 6 weeks, participants will learn foundational concepts, real-world applications, and practical tools to address climate change.

  • Generative AI Fundamentals
  • ESG Research
  • Climate Risk Analysis
  • Energy Consumption Optimization
  • Carbon Footprint Calculation

Overview

In this comprehensive course, you will explore the fundamentals of generative AI, its applications in climate change, and practical tools to enhance productivity. Through hands-on projects and expert insights, you will gain the skills needed to integrate AI into your ESG strategies effectively.

  • Web Streamline Icon: https://streamlinehq.com
    Online
    course location
  • Layers 1 Streamline Icon: https://streamlinehq.com
    English
    course language
  • Professional Certification
    upon course completion
  • Self-paced
    course format
  • Live classes
    delivered online

Who is this course for?

Sustainability and research teams

Professionals involved in sustainability and research who want to leverage generative AI in their ESG strategies.

Senior Leaders and Executives

Executives looking to understand the impact of generative AI on climate change and how to integrate it into their organizations.

Risk Management and Security Teams

Teams focused on risk management and security who need to understand the implications of generative AI in climate action.

This course offers key benefits such as understanding generative AI applications in climate change, practical tools for ESG strategies, and insights from industry experts. It is ideal for professionals looking to enhance their productivity and stay competitive in their jobs.

Pre-Requisites

1 / 3

  • Basic understanding of ESG principles

  • Familiarity with AI concepts

  • Interest in climate change and sustainability

What will you learn?

Week 1: Generative AI Fundamentals
This week explores the definition, the inner mechanisms, and the evolution of Generative AI.
Day 1: Definition of Generative AI
Learn the basic definition and concepts of Generative AI.
Day 2: Differences between traditional Machine Learning and Generative AI
Understand the key differences between traditional machine learning and generative AI.
Day 3: Transformers: a revolutionary breakthrough
Explore the concept of transformers and their impact on AI.
Day 4: Scaling transformers
Learn about the scaling of transformers and their applications.
Day 5: LLMs as a new human/machine interface
Understand how large language models (LLMs) serve as a new interface between humans and machines.
Week 2: The Landscape of Generative AI
This week discusses the Generative AI landscape and key players such as infrastructure providers, model providers, and application providers.
Day 6: Model providers
Learn about the key model providers in the generative AI landscape.
Day 7: Infrastructure providers
Understand the role of infrastructure providers in generative AI.
Day 8: Application providers
Explore the key application providers in the generative AI ecosystem.
Day 9: Hands-on project: Getting started with ChatGPT and Customer Personas
A practical project to get started with ChatGPT and create customer personas.
Day 10: Hands-on project: Analysing & extracting information from PDF Reports with AI
A hands-on project to analyze and extract information from PDF reports using AI.
Week 3: Current landscape of Generative AI in Climate Change
This week delves into the ESG domain and compares traditional approaches with AI-driven methods.
Day 11: Introduction and Background of Climate Change
Learn about the background and introduction to climate change.
Day 12: Current landscape of Generative AI in Climate Change
Understand the current landscape of generative AI in climate change.
Day 13: Current challenges in Climate Action
Explore the current challenges faced in climate action.
Day 14: Traditional vs AI-driven Approach
Compare traditional approaches with AI-driven methods in climate action.
Day 15: Expert interview: TBC
An expert interview to provide insights into generative AI and climate change.
Week 4: Applications and use cases of Generative AI in Climate Change
This week discusses Generative AI applications and current initiatives and use cases in Climate Change.
Day 16: Framework of Generative AI in Climate Change
Learn about the framework of generative AI in climate change.
Day 17: Practical Applications and Strategy
Explore practical applications and strategies for using generative AI in climate change.
Day 18: Case Study: Generative AI in Climate Risk Analysis
A case study on using generative AI for climate risk analysis.
Day 19: Case Study: Optimising Energy Consumption in City
A case study on optimizing energy consumption in a city using generative AI.
Day 20: Case Study: Earth-2 and Geospatial
A case study on Earth-2 and geospatial applications of generative AI.
Week 5: From Theory to Practice: Practical Approach
This week focuses on practical applications of generative AI tools in climate change.
Day 21: Navigate key Generative AI tools
Learn to navigate key generative AI tools.
Day 22: Hands-on project: Understanding Climate Change Concepts
A hands-on project to understand climate change concepts using AI.
Day 23: Hands-on project: Reporting Analysis with ChatGPT
A hands-on project to analyze reports using ChatGPT.
Day 24: Hands-on project: Carbon Footprint Calculation
A hands-on project to calculate carbon footprints using AI.
Day 25: Role of Cloud in Climate Action
Understand the role of cloud computing in climate action.
Week 6: Opportunity and risk in Climate Action
This week examines the advantages and key success factors of implementing AI in Climate Action and explores the regulation globally.
Day 26: Advantages / Key Success Factors of AI implementation in Climate Action
Learn about the advantages and key success factors of AI implementation in climate action.
Day 27: Need for Global AI Regulations
Understand the need for global AI regulations.
Day 28: Challenges
Explore the challenges faced in implementing AI in climate action.
Day 29: Ethical issues in Gen AI in Climate Action
Learn about the ethical issues in using generative AI for climate action.
Day 30: Expert interview: TBC
An expert interview to provide insights into the opportunities and risks in climate action.

What learners say about this course

  • “The content was really relevant. I really liked that it gave a lot of examples on how AI can be applied in the industry, the companies that are successful implementing AI and high level view on what AI is really about.”

    Magdalene Loh

    Senior Vice President and Head of Innovation at Prudential Singapore

  • “The interviews covered in the course introduced the insights that are very important from those with 20+ years experience professionals.”

    Priscilla Cournede

    Deputy Director at Life Reinsurance at Covéa

  • “Since I finished the course, I raised suggestions to my team to integrate different technologies and AI in the different parts of the organisation.”

    Goh Theng Kiat

    Chief Customer Officer at Prudential Singapore

Upcoming cohorts

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£270