Machine Learning in Finance: Time Series Forecasting in Python – Free Full Day Workshop
Saturday 24th November
HSBC Bank Plc, Canada Square, London
Learn the Fundamentals of Machine Learning and Time Series Forecasting in Finance
Exclusively available for UK university students, HSBC Global Banking and Markets and Cambridge Spark invite you to attend a FREE full-day workshop, introducing you to the fundamentals of Time Series forecasting in Python, enabling you to learn how to use global time series data to your advantage to forecast stock performance.
What you will learn
Most financial data is available in time series form. The time dimensionality introduces interesting challenges for machine learning as data points taken over time may have an internal structure and characteristics.
In this hands-on workshop you will learn:
- How to work with Date and Time in Python (numpy, pandas)
- An introduction to Time Series Theory
- Common Time Series exploration techniques such as window functions, lag functions and autocorrelation
- How to visualise Time Series Data in Python
- The foundation behind autoregressive models (AR)
- How to work with Autoregressive–moving-average model (ARMA)
- How to work with Facebook’s Prophet library for scalable Time Series Analysis
The seminar will conclude with a competition where you will get to implement your own predictive model in Python on a new dataset.
Meet the HSBC team
On the day, you’ll have the opportunity to meet and network with Data Science leaders at HSBC, as well as learn about internship and graduate opportunities to take your career forward as a Data Scientist.
Connect with the team below.
Matthew Sattler – Global Head of Data Science at HSBC Global Banking and Markets
James Bickerton – Global Head of Operational Strategy, Global Banking and Markets
Dr. Elena Chatzimichali – Data Scientist, Corporate and Institutional Digital
Dr. Ash Booth – Head of Artificial Intelligence, Corporate and Institutional Digital
Gregory Springett – Lead Data Scientist, Global Banking and Markets
Dr. Oxana Samko – Senior Data Subject Matter Expert, Applied Innovation & Strategic Investments
Jonathan Poole – Production Support Analyst, Global Banking and Markets
Dr. Pedro Baiz – Data Scientist, Corporate and institutional Digital, Royal Society Entrepreneur in Residence
Dr. Christopher Jones – Quantitative Research/Data Scientist – Equities – Global Banking and Markets
Elena Nemtseva – Data Scientist, Client Profitability and Portfolio Analytics Technology, Global Banking and Markets
Nikolas Kuhlen – Data Scientist, Global Banking and Markets, Doctoral Student at The Alan Turing Institute
Dr. Mehtab Pathan – Data Scientist, Research Analytics, Financial Crime Threat Mitigation
This workshop is aimed at university Students looking for internships and graduates roles in Data Science and Machine Learning in the Finance Industry.
You should be at least a second-year student and have an academic background in:
- Computer Science
You should also be comfortable coding in Matlab, R or preferably Python as it is the programming language used during the workshop.
- You will need to complete the application form and submit your CV below by 14th November
- You will be asked to conduct a series of Python and Maths preparatory exercises to confirm your place
- Your application will be reviewed and you will receive confirmation that you have secured a place on the workshop on the 21st November
Please complete the form to apply
We’ll follow up to confirm we’ve received your submission and send you details regarding the preparatory exercises
HSBC is one of the world’s leading banks, with a network covering 66 countries and territories. Our size and global reach mean we offer many ways for you to develop your career. HSBC Global Banking and Markets provides financial services and products to corporates, governments and institutions – partnering with them to help them achieve consistent, long-term performance while delivering commercial opportunities in both developing and developed markets.