Skip to content

Artificial Intelligence for Trading

Nanodegree Program

Complete real-world projects designed by industry experts, covering topics from asset management to trading signal generation. Master AI algorithms for trading, and build your career-ready portfolio.

Enroll Now

04Days06Hrs56Min38Sec

  • Estimated time
    6 Months

    At 10 hrs/week

  • Enroll by
    September 28, 2022

    Get access to classroom immediately on enrollment

  • Prerequisites
    Python & Mathematics
Built in partnership with
  • WorldQuant

What you will learn

  1. Quantitative Trading

    Estimated 6 months to complete

    Learn the basics of quantitative analysis, including data processing, trading signal generation, and portfolio management. Use Python to work with historical stock data, develop trading strategies, and construct a multi-factor model with optimization.

    Prerequisite knowledge

    1. Basic Quantitative Trading

      Learn about market mechanics and how to generate signals with stock data. Work on developing a momentum-trading strategy in your first project.

    2. Advanced Quantitative Trading

      Learn the quant workflow for signal generation, and apply advanced quantitative methods commonly used in trading.

    3. Stocks, Indices, and ETFs

      Learn about portfolio optimization, and financial securities formed by stocks, including market indices, vanilla ETFs, and Smart Beta ETFs.

    4. Factor Investing and Alpha Research

      Learn about alpha and risk factors, and construct a portfolio with advanced optimization techniques.

    5. Sentiment Analysis with Natural Language Processing

      Learn the fundamentals of text processing, and analyze corporate filings to generate sentiment-based trading signals.

    6. Advanced Natural Language Processing with Deep Learning

      Learn to apply deep learning in quantitative analysis and use recurrent neural networks and long short-term memory to generate trading signals.

    7. Combining Multiple Signals

      Learn advanced techniques to select and combine the factors you’ve generated from both traditional and alternative data.

    8. Simulating Trades with Historical Data

      Learn to refine trading signals by running rigorous back tests. Track your P&L while your algorithm buys and sells.

All our programs include:

  • Real-world projects from industry experts

    With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.

  • Technical mentor support

    Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you, and keeping you on track.

  • Career services

    You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.

  • Flexible learning program

    Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.

Program offerings

  • Class content

    • Content co-created with WorldQuant
    • Real-world projects
    • Project reviews
    • Project feedback from experienced reviewers
  • Student services

    • Technical mentor support
    • Student community
  • Career services

    • Github review
    • Linkedin profile optimization

Succeed with personalized services.

We provide services customized for your needs at every step of your learning journey to ensure your success.

Get timely feedback on your projects.

  • Personalized feedback
  • Unlimited submissions and feedback loops
  • Practical tips and industry best practices
  • Additional suggested resources to improve
  • 1,400+

    project reviewers

  • 2.7M

    projects reviewed

  • 88/100

    reviewer rating

  • 1.1 hours

    avg project review turnaround time

Mentors available to answer your questions.

  • Support for all your technical questions
  • Questions answered quickly by our team of technical mentors
  • 1,400+

    technical mentors

  • 0.85 hours

    median response time

Learn with the best.

Learn with the best.

  • Cindy Lin

    Curriculum Lead

    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 Chakraborty

    Instructor

    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 Otto Hamel

    Instructor

    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 Shyu

    Instructor

    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 Bucholtz

    Instructor

    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.

  • Parnian Barekatain

    Instructor

    Parnian is a self-taught AI programmer and researcher. Previously, she interned at OpenAI on multi-agent Reinforcement Learning and organized the first OpenAI hackathon. She also runs a ShannonLabs fellowship to support the next generation of independent researchers.

  • Juan Delgado

    Content Developer

    Juan is a computational physicist with a Masters in Astronomy. He is finishing his PhD in Biophysics. He previously worked at NASA developing space instruments and writing software to analyze large amounts of scientific data using machine learning techniques.

  • Luis Serrano

    Instructor

    Luis was formerly a Machine Learning Engineer at Google. He holds a PhD in mathematics from the University of Michigan, and a Postdoctoral Fellowship at the University of Quebec at Montreal.

  • Cezanne Camacho

    Curriculum Lead

    Cezanne is a machine learning educator with a Masters in Electrical Engineering from Stanford University. As a former researcher in genomics and biomedical imaging, she’s applied machine learning to medical diagnostic applications.

  • Mat Leonard

    Instructor

    Mat is a former physicist, research neuroscientist, and data scientist. He did his PhD and Postdoctoral Fellowship at the University of California, Berkeley.

Top student reviews

 
0.0 stars
(0)
 
NaN stars

        

 
NaN stars

        

 
NaN stars

        

 
NaN stars

        

 
NaN stars

        

 
NaN stars

        

AI for Trading

Get started today

  • Monthly access

    Pay as you go


    per

    /

    /

    Enroll now
    • Maximum flexibility to learn at your own pace.
    • Cancel anytime.
  • - access

    Pay upfront and save an extra 0%


    for - access

    Enroll now
    • Save an extra 0% vs. pay as you go.
    • 6 months is the average time to complete this course.
    • Switch to monthly price after if more time is needed.
    • Cancel anytime.
    Best Value
  • Learn

    Learn the basics of quantitative analysis, and work on real-world projects from trading strategies to portfolio optimization.
  • Average Time

    On average, successful students take 6 months to complete this program.
  • Benefits include

    • Real-world projects from industry experts
    • Technical mentor support
    • Career services

Program details

Program overview: Why should I take this program?
  • Why should I enroll?
  • What jobs will this program prepare me for?
  • How do I know if this program is right for me?
Enrollment and admission
  • Do I need to apply? What are the admission criteria?
  • What are the prerequisites for enrollment?
  • If I do not meet the requirements to enroll, what should I do?
Tuition and term of program
  • How is this Nanodegree program structured?
  • How long is this Nanodegree program?
  • Can I switch my start date? Can I get a refund?
Software and hardware: What do I need for this program?
  • What software and versions will I need in this program?

Artificial Intelligence for Trading

Enroll Now