Python applications in financial services

  • Data and technology, AI and machine learning
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Key reasons to attend 

  • Learn to use Python effectively in a variety of financial risk settings 
  • Explore practical use cases including data analysis and library creation 
  • Apply theory into practice with structured tutorials 

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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

This expert-led learning event will equip participants with the practical skills and knowledge to effectively use Python in a variety of financial risk settings.

Participants will explore the many features of Python and practical use cases within financial markets, including data analysis and library creation. With a hands-on Python tutorial at the end of each day, this dynamic course will provide participants with the opportunity to apply the theory shared in the main sessions, as well as engage in live interaction and questions with the course expert. 

By the end of the course, participants will have learned the necessary tools to facilitate successful programming, data considerations and backtesting in line with best market practice in the financial industry.


Pricing options:

  • Early-bird rate: save up to $800 per person by booking in advance (refer to the booking section for the deadline)
  • 3-for-2 rate: save over $2,000 by booking a group of three attendees (applicable to this course)
  • Subscriber reward: save 30% off the standard rate if you are a Risk.net subscriber (use code SUB30)
  • Season tickets: save over $1,000 per person by booking 10 or more tickets (available on selection of courses)

*The 30% subscriber reward discount is applicable only to current Risk.net subscribers. If this criteria is not met, we reserve the right to cancel the booking and issue an invoice for the correct rate. Discounts cannot be applied to already registered participants.

Learning objectives

  • Master the basics and fundamentals of Python
  • Visualise data libraries using different programmes 
  • Identify the types of financial data used for analysis
  • Discuss the key considerations for creating a trading strategy
  • Recognise the behaviour of foreign exchange around major data events
  • Develop skills of Python use through tutorials and case studies 

Who should attend

Relevant departments may include but are not limited to:

  • Financial data 
  • Python 
  • Data analysis  
  • Machine learning  

Agenda

September 9–11, 2024

Live online. Timezones: Emea/Americas

Sessions:

  • Introduction to Python I 
  • Tutorial for introduction to Python I 
  • Data analysis in Python 
  • Tutorial for data analysis in Python  
  • Analysis of financial data 
  • Tutorial for analysis of financial data 
  • Financial market case studies using Python 
  • Tutorial for financial market case studies using Python 

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Tutors

Saeed Amen

Co-founder

Turnleaf Analytics

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Saeed is a co-founder of Turnleaf Analytics, where they use innovative approaches including alternative data and machine learning to create macroeconomic forecasts, in particular for inflation which are available for client subscription, and have beaten the benchmark in over 60% of cases since live publication.

He has developed algorithmic trading strategies at Lehman Brothers (where he co-developed MarQCuS which had $2bn AUM), Nomura and independently. He has profitably run systematic trading models for market making trading desks. Clients have included Bloomberg, Accenture, CLS, Freepoint Commodities, RavenPack, Cytora, Investopedia, a Chicago prop firm, a large European asset manager and several UK quant hedge funds.

Saeed is an author and has written Trading Thalesians - What the ancient world can teach about trading today (Palgrave Macmillan) and has co-authored The Book of Alternative Data (Wiley). He is also the founder of Cuemacro, co-founder of Thalesians and a visiting lecturer at Queen Mary University of London.

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

September 9–11, 2025

Online, Emea/Americas

Price

$3,199

Early-bird Price

$2,399
Ends August 8
Book now

Enquire about:

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

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