Generative AI masterclass

  • AI and machine learning
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Key reasons to attend

  • Learn use cases of generative artificial intelligence (GenAI)
  • Explore the implications of GenAI hallucinations  
  • Address the importance of neural networks architecture 

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Customised solutions

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Working with the portfolio of expert tutors and Risk.net’s editorial team, we can develop and deliver a customised learning to make the most impact for your team, from initial assessment to final review. 

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About the course

Join us on this virtual masterclass to gain a robust understanding of GenAI. Participants will deep dive into the technicalities of GenAI by studying the mathematics of ANNs and the ethical aspects of managing AI.  

Key sessions will cover fundamental topics that provide diverse views of GenAI from a financial industry perspective. Attention mechanisms in LLM frameworks will also be explored.    

Participants will engage in practical case studies and discussions alongside their peers and the expert tutor, while learning how to navigate the opportunities and risks of this rapidly changing technology.  


Pricing options:

  • Early-bird rate: save up to $800 per person by booking in advance*
  • 3-for-2 rate: save over $2,000 by booking a group of three attendees*
  • Subscriber reward: save 30% off the standard rate if you are a Risk.net subscriber*
  • Season tickets: cost-effective option for groups of 10 or more. Learn more

*T&Cs apply
 

Learning objectives

  • Apply GenAI by studying a sample Python notebook
  • Evaluate large language models (LLMs) and their basic criteria
  • Determine how to construct a LangChain and a LangGraph
  • Assess artificial neural network (ANN) frameworks
  • Navigate how to achieve more complex and sophisticated outputs  
  • Align on the legal and key ethical aspects of AI 

Who should attend

Relevant departments may include, but are not limited to:

  • Risk management
  • AI
  • Machine learning
  • Compliance
  • Regulation
  • IT and data management
  • Chief information security officers
  • Innovation
  • Risk technology

Agenda

November 25–26, 2024

Live online. Timezones: Emea/Apac

Sessions:

  • An overview of artificial neural networks (ANNs)    
  • Introduction to large language models (LLMs)
  • LangChain and LangGraphs  
  • Case study on trading floor

Tutor:

  • Sunil Verma, Front office quant supporting business decision making, Citi

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Tutors

Sunil Verma

Front office quant supporting business decision making

Citi

View bio

Sunil is a former risk and front office quant and is now embedded in a desk responsible for in-business risk management within Citi Markets. He has held multiple positions within investment banking and has been largely focussed on market and counterparty risk related modelling activities. He has also worked extensively on business efficiency and regulatory focussed projects.

He has over 20 years of experience in the industry in various roles involving mathematical modelling, coding, project management, team coaching, etc.

Sunil was previously working at UBS and headed their market risk stress testing initiatives. He is a hands-on quant with Python being his coding language of choice.

Sunil’s qualifications include an Engineering degree and an MBA from IIT Mumbai. He lives in London and enjoys walks with his dog.

Accreditation

This course is CPD (Continued Professional Development) accredited. One credit is awarded for every hour of learning at the event.

Pre-reading materials

The Risk.net resources below have been selected to enhance your learning experience:

A Risk.net subscription will provide you access to these articles. Alternatively, register for free to read two news articles a month 

Registration

November 25–26, 2024

Online, Emea/Apac

Price

$2,999
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Enquire about:

  • Agenda and registration process
  • Group booking rates
  • Customisation of this programme
  • Season tickets options

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