Artificial Intelligence for Trading Nanodegree
Written by Sue Gee   
Monday, 06 August 2018

In partnership with WorldQuant, Udacity has a new Artificial Intelligence for Trading Nanodegree program. Applications are now open for the first cohort which begins on August 21st.

Udacity launched its School of AI back in March with three new Nanodegree programs, AI Programming with Python,  Computer Vision and Natural Language Processing, also announcing one in Reinforcement Learning which starts on August 28th.

Now it has added another "applied AI" program focused on the potentially lucrative area of financial trading. The program, which has been developed in collaboration with top industry professionals with prior experience at JPMorgan, Morgan Stanley, and Millennium Management has been designed to enable students to learn the latest AI applications in trading and quantitative finance through building a portfolio of real-world projects. Over the course of two 3-month terms students will build financial models with real data, and learn to generate trading signals using natural language processing, recurrent neural networks, and random forests.

udacity tradingai banner 

According its blurb:

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. 

The program is made up of two terms, each of three months. The first term covers the basics of quantitative analysis, covering data processing, trading signal generation, and portfolio management. Python will be used to work with historical stock data, develop trading strategies, and construct a multi-factor model with optimization. Featured projects include: 

  • Trading with Momentum: Learn to implement  momentum-trading strategies and test if they have the potential to be profitable.
  • Smart Beta and Portfolio Optimization: Create two portfolios utilizing smart beta methodology and optimization, and evaluate the performance of the portfolios by calculating tracking errors.   
  • Multi-factor Model: Research and generate multiple alpha factors and apply various techniques to evaluate performance, and learn to pick the best factors for your portfolio. 

The second term is focused on AI Algorithms for Trading. Students will work with alternative data, use machine learning to generate trading signals, run backtests to evaluate trading signals and use advanced techniques to combine top performers. Featured projects include: 

  • Sentiment Analysis using NLP: Apply natural language processing on corporate filings, such as 10Q and 10K statements, covering everything from cleaning data and text processing to feature extraction and modeling.
  • Deep Neural Network with News Data: Build deep neural networks to process and interpret news data. Construct and train LSTM networks for sentiment classification, run backtests, and apply financial models to news data for signal generation.   
  • Combine Trading Signals for Enhanced Alpha: Create a prediction model for the S&P 500 and its constituent stocks by performing model selection for a large data set, which includes market, fundamental, and alternative data.

Term 1 is open for enrollment now at a cost of $999. To succeed in the program, you will need some experience programming with Python, and familiarity with statistics, linear algebra and calculus. No prior experience in finance is required - however a keen interest in this area would seem to be very necessary. While Udacity no longer makes any guarantees with regard to employment on successful completion of any of its programs, WorldQuant is pledging to consider graduates for job opportunities at the firm from among graduates of the program. 

udacity trading sqMore Information

Introducing the Artificial Intelligence for Trading Nanodegree Program

Artificial Intelligence for Trading Nanodegree

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Last Updated ( Tuesday, 07 August 2018 )