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CFTE

Generative AI for Cybersecurity in Financial Services

  • up to 6 weeks
  • Intermediate

This course provides a comprehensive understanding of how generative AI can be leveraged in cybersecurity within financial services. Participants will learn about threat detection, threat intelligence, and the practical use of AI tools, enhancing their skills and protecting their organizations.

  • Generative AI Fundamentals
  • Cybersecurity Landscape
  • AI-driven Threat Detection
  • Predictive Analytics
  • Data Management

Overview

In this course, you will master the fundamentals of generative AI and its applications in cybersecurity. You will explore real-world AI applications, learn to use cutting-edge AI tools for threat detection and predictive analytics, and understand the ethical considerations and regulations surrounding AI. The course includes hands-on projects and expert interviews to provide practical insights and strategies for implementing AI in your organization.

  • 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?

Chief Information Security Officers

Professionals responsible for overseeing and managing the cybersecurity strategy and operations within an organization.

Information Security Managers

Managers who ensure the security of information systems and data within an organization.

Security Architects

Experts who design and implement security systems to protect an organization's IT infrastructure.

This course offers key benefits such as mastering generative AI for cybersecurity, understanding real-world applications, and learning from industry experts. It is designed for professionals in financial services who want to enhance their skills and protect their organizations from cyber threats.

Pre-Requisites

1 / 3

  • Basic understanding of cybersecurity principles

  • Familiarity with AI and machine learning concepts

  • Experience in financial services or related industries

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
Understand what Generative AI is and its key characteristics.
Day 2: Differences between traditional Machine Learning and Generative AI
Learn the distinctions 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
Understand how transformers can be scaled for various applications.
Day 5: LLMs as a new human/machine interface
Learn about large language models and their role 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
Identify the key model providers in the Generative AI space.
Day 7: Infrastructure providers
Learn about the infrastructure providers that support Generative AI.
Day 8: Application providers
Explore the application providers that leverage Generative AI.
Day 9: Hands-on project: Getting started with ChatGPT and Customer Personas
Engage in a hands-on project to get started with ChatGPT and create customer personas.
Day 10: Hands-on project: Analysing & extracting information from PDF Reports with AI
Learn to analyze and extract information from PDF reports using AI.
Week 3: Landscape of GenAI in Cybersecurity
This week delves into the Cybersecurity domain and compares traditional approaches with AI-driven methods.
Day 11: Introduction and background of Cybersecurity
Get an introduction to the field of cybersecurity and its background.
Day 12: Challenges in Cybersecurity
Understand the key challenges faced in cybersecurity.
Day 13: Traditional approaches vs AI-driven approaches in Cybersecurity
Compare traditional cybersecurity approaches with AI-driven methods.
Day 14: Current landscape of Generative AI in Cybersecurity
Explore the current landscape of Generative AI in cybersecurity.
Day 15: Expert interview: TBC
Listen to an expert interview on the topic (to be confirmed).
Week 4: Use cases of GenAI in Cybersecurity
This week discusses Generative AI applications and current initiatives and use cases in Cybersecurity.
Day 16: Framework of Generative AI in Cybersecurity in Financial Services
Learn about the framework of Generative AI in cybersecurity within financial services.
Day 17: Current applications of Generative AI in Cybersecurity
Explore the current applications of Generative AI in cybersecurity.
Day 18: Case studies on IBM, HSBC and JPMorgan
Review case studies on the use of Generative AI in cybersecurity by IBM, HSBC, and JPMorgan.
Day 19: Case studies on healthcare cyber resilience and BT Group
Examine case studies on healthcare cyber resilience and BT Group.
Day 20: Expert interview (TBC)
Listen to an expert interview on the topic (to be confirmed).
Week 5: From Theory to Practice
This week focuses on practical applications of generative AI tools in Cybersecurity.
Day 21: Navigate key Generative AI tools
Learn to navigate key Generative AI tools.
Day 22: Understanding the Prompt Engineering
Understand the concept of prompt engineering in AI.
Day 23: Using Athena to detect phishing email
Learn to use Athena for detecting phishing emails.
Day 24: Using Athena for risk mitigation
Explore how to use Athena for risk mitigation.
Day 25: ChatGPT for threat identification
Learn to use ChatGPT for identifying threats.
Day 26: AI for organisations’ cyber security resilience
Understand how AI can enhance an organization's cybersecurity resilience.
Week 6: Opportunities & risks in Cybersecurity
This week examines the advantages and key success factors of implementing AI in Cybersecurity and teaches the privacy and data usage in Generative AI in Cybersecurity.
Day 27: Key Success Factors of integrating AI in Cybersecurity
Learn about the key success factors for integrating AI in cybersecurity.
Day 28: AI and Gen AI Regulations
Understand the regulations surrounding AI and Generative AI.
Day 29: Data, Risk, Privacy, Ethical considerations & Challenges
Explore data management, risk, privacy, ethical considerations, and challenges in AI.
Day 30: Changes in skills & Future outlook
Understand the changes in required skills and the future outlook of AI in cybersecurity.

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

Meet your instructors

  • Huy Nguyen Trieu

    Co-Founder & Programme Director, CFTE

    Huy Nguyen Trieu is the Co-Founder and Programme Director of CFTE, a global Fintech education platform. He is an entrepreneur, academic, investor, and banker with extensive experience in the financial industry.

  • Danny Lopez

    CEO, Glasswall

    Danny Lopez is a proven and versatile leader with a track record of success as a banker, senior diplomat, C-level exec and advisor. He thrives in dynamic, innovative, results-driven environments with a strong sense of culture and values.

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