Study 10 hrs/week and complete in 6 months
In this program, you’ll analyze real data and build financial models for trading. Whether you want to pursue a new job in finance, launch yourself on the path to a quant trading career, or master the latest AI applications in quantitative finance, this program offers you the opportunity to master valuable data and AI skills.
We collaborated with WorldQuant and top industry professionals with prior experience at JPMorgan, Morgan Stanley, and Millennium Management to ensure you learn the latest AI applications in trading and quantitative finance.
Advance your finance knowledge, and build a strong portfolio of real-world projects. Build financial models with real data, and learn to generate trading signals using natural language processing, recurrent neural networks, and random forests.
Your assigned in-classroom mentor will provide feedback on your projects and support you throughout your learning journey. You'll also be part of a supportive peer community.
Connect with finance professionals who have worked at top hedge funds, investment banks, and Fintech startups, who can provide you with actionable insights and guidance.
Jonathan has previously held leadership roles such as Global Head of Equities at Millennium Management and Co-Head of Americas Equity Derivatives Trading at JPMorgan.
Kendall has been a quant trader and researcher at Citadel, Millennium Partners and JPMorgan. He has an MS in Financial Math from Stanford University.
Murat is a quant researcher at Radix Trading and has worked for JP Morgan and Citadel. He has a PhD in Statistics from Stanford University.
Justin has been an investment strategist in the Scientific Active Equity Group at BlackRock, and a quant research analyst at MUFG/HighMark Capital.
Harry has worked on algorithmic trading programs and risk management at Morgan Stanley and Apogee Fund Management, and as CTO at Carlyle Blue Wave.
Cindy is a quantitative analyst with experience working for financial institutions such as Bank of America Merrill Lynch, Morgan Stanley, and Ping An Securities. She has an MS in Computational Finance from Carnegie Mellon University.
Arpan is a computer scientist with a PhD from North Carolina State University. He teaches at Georgia Tech (within the Masters in Computer Science program), and is a coauthor of the book Practical Graph Mining with R.
Elizabeth received her PhD in Applied Physics from Stanford University, where she used optical and analytical techniques to study activity patterns of large ensembles of neurons. She formerly taught data science at The Data Incubator.
Eddy has worked at BlackRock, Thomson Reuters, and Morgan Stanley, and has an MS in Financial Engineering from HEC Lausanne. Eddy taught data analytics at UC Berkeley and contributed to Udacity’s Self-Driving Car program.
Brok has a background of over five years of software engineering experience from companies like Optimal Blue. Brok has built Udacity projects for the Self Driving Car, Deep Learning, and AI Nanodegree programs.
This program was built in collaboration with WorldQuant, and top professionals from leading financial institutions, to ensure your long-term success in quantitative finance. The skills you learn will prepare you for a wide range of quant finance jobs in hedge funds, investment banks, and FinTech startups.Designed to prepare you for career success in quantitative finance.
Create your professional portfolio with Udacity and open up a world of opportunities. Our hiring partners are eager to meet you.Create your portfolio and open up a world of opportunities.
Work with experienced career professionals to improve your job search, and impress recruiters. Get valuable feedback on your LinkedIn profile and your professional brand.Work with career professionals to impress recruiters.
40,000+ highly-skilled grads make up your new career community. Ready to collaborate, share referrals, or hire your own team? The Udacity Alumni Network is here for you!Connect with our global community to grow your career.
To make it even easier to learn, you can finance your Nanodegree through Affirm.
As low as US$84 per month at 0% APR.
Pay your monthly bill using a bank transfer, check, or debit card.
Learn the basics of quantitative analysis, and work on real-world projects from trading strategies to portfolio optimization.
Demand for quantitative talent is growing at incredible rates. Data-driven traders are now responsible for more than 30% of all US stock trades by investors (or about $1 trillion USD worth of investments, up from 14% in 2013). This scenario represents incredible opportunity for individuals eager to apply cutting-edge technologies to trading and finance.
Whether you want to pursue a new job in finance, launch yourself on the path to a quant trading career, or master the latest AI applications in trading and quantitative finance, this program will give you the opportunity to build an impressive portfolio of real-world projects. You will build financial models on real data, and work on your own trading strategies using natural language processing, recurrent neural networks, and random forests. You’ll also enjoy direct access to leading experts in the field, and get personalized project and career support.
To create the curriculum for this program, we collaborated with WorldQuant, a global quantitative asset management firm, as well as top industry professionals with prior experience at JPMorgan, Morgan Stanley, Millennium Management, and more. If your goal is to learn from the leaders in the field, and to master the most valuable and in-demand skills, this program is an ideal choice for you.
Graduates of this program will have the quantitative skills needed to be extremely valuable across many functions, and in many roles at hedge funds, investment banks, and FinTech startups.
Specific roles include:
If you’re a programmer, data analyst or someone with a strong quantitative background, this program offers you the ideal path to pursue a quant trading career and prepares you to seek out data science jobs across the financial ecosystem.
No. This Nanodegree program accepts all applicants regardless of experience and specific background.
The Artificial Intelligence for Trading Nanodegree program is designed for students with intermediate experience programming with Python and familiarity with statistics, linear algebra and calculus. In order to successfully complete this program, you should meet the following prerequisites:
Calculus and linear algebra
The Artificial Intelligence for Trading Nanodegree program is composed of two (2) three (3)-month terms. Each term has fixed start and end dates.
Students must complete both terms and all projects to graduate from the Nanodegree program. Each project will be reviewed by the Udacity reviewer network. Feedback will be provided, and if you do not pass the project, you will be asked to resubmit the project until it passes.
Please see the Udacity Nanodegree program FAQs found here for policies on enrollment in our programs.
To successfully complete this Nanodegree program, you’ll need to be able to download and run Python 3.7.