About this course

Our three-day course is an introduction to data science and the Python programming language, exploring many of the key libraries and tools commonly used in the financial services industry. Aimed at finance professionals, the course builds real solutions for data analysis using Pandas, visualisation using Matplotlib and Plot.ly, and n-dimensional matrix manipulation and linear algebra using Numpy.

Who can benefit from the course?

This course is of benefit to business analysts, quantitative analysts, sales and marketing, financial software developers and any professional seeking to perform data analysis. Prior knowledge of Python is not required.

What will you learn?

The course spans three days, during which time you will learn:

• The basics of the Python programming language
• How to consume market data and extract relevant features
• How to perform transformations on data
• How to work with financial time series data
• How to build pricing and simple predictive models
• How to visualize your data with professional looking charts and graphs
• How to perform technical analysis and back-testing of models

How will you learn it?

This course is hands-on. There are multiple labs that will explore different aspects of financial analysis, including:

• How to consume financial data from spreadsheets and the Internet, construct a collection of portfolios and export them to a spreadsheet.
• How to produce a chart of Bollinger bands from market data.
• How to use Pandas to consume financial data and perform analysis including slicing into date ranges, down sampling and up sampling, interpolation, moving time windows and aggregation.
• How to construct professional price/volume charts.
• How to consume poorly formatted market data, perform re-indexing and transformations to provide a clean data set, apply analysis to the data and re-export to a spreadsheet.
• How to calculate the alpha and beta values from a given portfolio to show the return on investment as compared to a traditional market index and measure its volatility.
• How to use Python to create programs to consume, transform, analyse and export data.
• How to perform technical analysis to choose a set of symbols between data ranges, build a trading strategy, execute back-testing to validate the strategy and produce a report to show the best to worse cases for the symbol and the strategy.

Students have the option of bringing and using their own laptops so that the complete working enviroment can be easily transported.

This course is supported by two instructors, each with extensive experience of technology within financial services. Mallon Associates' courses are highly interactive with instructors teaching together, answering questions, exploring ideas and providing one-on-one guidance throughout the lab work.

Braun is a leader in data analysis and visualisation, deep learning and machine intelligence, and a senior instructor within the team. Working on tax, financial and trading system for governments, banks and exchanges, Braun brings expert skills honed over more than two decades of experience.

Pat is a seasoned developer and instructor, with extensive experience of cash and derivatives desks in various trading functions across Equities, FX and Fixed Income. Having worked with the NYSE and in senior positions with many tier 1 banks in London, Pat now supports Mallon Associates’ training activities in the world's leading financial centres.