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Can't travel? Don't want to travel? LFS LiveLFS Live brings the class to you!

  • Live interactive training from world renowned practitioners in the comfort of your own home
  • Real classroom experience without the inconvenience of travel
  • World class teaching from the comfort of your preferred location

Please contact us for more information at info@londonfs.com.

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Python for Finance

Python is a general programming language which can be used to build web applications, websites or even complex applications. The most important part of Python is its syntax which is considered to be close to the original mathematics syntax. This makes it quite flexible in playing around with numbers, making it a very useful tool for data analysis, risk management, automatic trading and other financial applications.

During the course, the delegates will focus on practical applications of the programme in the area of finance and risk through workshops and working examples.

No programming experience is required.

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  • Date:
  • Venue:
  • This course is only available via LFS LiveLFS Live
  • Fee:
  • £1345 per day
    £2690 total

This course is also available in New York Time Zone and Singapore Time Zone

Who The Course is For

This course is primarily aimed at those working in financial institutions, regulatory bodies, advisory firms and technology vendors. Specific job titles may include but are not limited to:

  • Trading
  • Portfolio management
  • Asset allocation
  • Data science
  • Financial engineering
  • Quantitative analytics
  • Quantitative modelling
  • Infrastructure and technology
Learning Objectives
  • Learn the capabilities of Python regarding financial applications
  • Become familiar with the programming language and the system of modules and tools
  • Understand the various data structures in Python
  • Learn about Jupyter Notebooks
  • Get to grips with the various applications of Python – graphs, automated reports, financial data
  • Discover how to create & edit spreadsheets with Python
  • Become familiar with environment management in Python
  • Be introduced to the machine learning library (scikit-learn) of Python
Prior Knowledge
  • Basic notions of statistics
  • Good working knowledge of Excel
  • Elementary knowledge of a programming language (Matlab, VBA,…) helps but no knowledge of Python is required

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