
Take human bias out of the equation with automated trading.
6 weeks entirely online, excluding orientation
Self-paced weekly modules, 8–10 hours per week
Learn alongside a global cohort of like-minded professionals
89% learner satisfaction
A comprehensive overview of algorithmic trading, including its history, benefits, challenges, rules, and processes.
The skills required to plan and implement your own algorithmic trading strategies, and assess the efficacy of a trading model in a real-world market environment.
An informed view on the future of systematic trading and how it’s impacted by emerging technologies such as artificial intelligence and machine learning.
Knowledge, insights, and frameworks from University of Oxford faculty, and a host of international industry experts.
Eager to understand what algorithmic trading strategies have to offer you as a trader, investor, or financial professional
A business leader who wants to leverage algorithmic trading in your firm
Interested in the strategic and technical side of algorithmic trading and the creation of rule-driven trading models
In the early stages of your career at a quantitative finance firm and keen to explore the world of automated trading
A risk, compliance, or legal professional seeking to improve your professional knowledge of algorithmic trading and its regulatory framework

While this programme provides a non-technical introduction to the world of algorithmic trading, it also features optional activities for participants interested in building an algorithmic trading model using Python. These exercises present a unique opportunity to bridge the gap between the programme’s theoretical content and real-world market applications. Once on the programme, you’ll have the choice to complete these activities as they will not count towards your grades. No extra software is required.
Over the duration of this online programme, you’ll work through the following modules:
Nir Vulkan
Associate Professor of Business Economics, Saïd Business School, University of Oxford
Professor Nir Vulkan is an authority on e-commerce and market design, and on applied research and teaching on hedge funds. His expertise lies in crowdfunding, e-commerce, market design, entrepreneurship, hedge funds, and fintech. Nir has been a lecturer at Saïd Business School since 2001. He was the director of the Oxford Centre for Entrepreneurship and Innovation (OxCEI) and the co-founder and director of OxLab, a laboratory for social science experiments, both at Saїd Business School.
This Oxford Digital Marketing: Disruptive Strategy Programme is certified by the United Kingdom CPD Certification Service, and may be applicable to individuals who are members of, or are associated with, UK-based professional bodies. The programme has an estimated 80 hours of learning.
Note: should you wish to claim CPD activity, the onus is on you. Oxford Saïd and GetSmarter accept no responsibility, and cannot be held responsible, for the claiming or validation of hours or points.

This programme combines esteemed academics and leading industry players to ensure that you get a full 360-degree perspective on algo trading.
“The programme has afforded me the base knowledge needed to develop and expand my algo skill set. I would recommend it to anyone looking to start a career in algo trading, but who has no idea where to begin.”
– Stephen O., Quant Analyst and Algo Trader, Virgin Money
This Oxford Algorithmic Trading Programme is delivered in collaboration with online education provider GetSmarter. Join a growing community of global professionals, and benefit from the opportunity to:
Experience a flexible but structured approach to online education as you plan your learning around your life to meet weekly milestones.
Enjoy a personalised, people-mediated online learning experience created to make you feel supported at every step.
Earn a certificate of attendance recognising your online programme from Saïd Business School, University of Oxford.
Enter your information to access the programme prospectus and learn more about this course from GetSmarter.