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Udacity

Artificial Intelligence for Trading

WorldQuant via Udacity Nanodegree

Overview

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.
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.

Syllabus

  • 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.

    Trading with momentum
  • Advanced Quantitative Trading

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

    Breakout Strategy
  • Stocks, Indices, and ETFs

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

    Smart Beta and Portfolio Optimization
  • Factor Investing and Alpha Research

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

    Alpha Research and Factor Modeling
  • Sentiment Analysis with Natural Language Processing

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

    Sentiment Analysis using NLP
  • 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.

    Deep Neural Network with News Data
  • Combining Multiple Signals

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

    Combine Signals for Enhanced Alpha
  • 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.

    Backtesting

Taught by

Cindy Lin, Arpan Chakraborty, Elizabeth Otto Hamel, Eddy Shyu, Brok Bucholtz, Parnian Barekatain, Juan Delgado, Luis Serrano, Cezanne Camacho, Mat Leonard, Eduardo P., Hsin-Wen C., Frank Salvador Y., Sridhar S., Jonnie W. and André V.

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Reviews

4.0 rating, based on 1 reviews

Start your review of Artificial Intelligence for Trading

  • Taher Elhassan
    "Well till now it is very interesting , although the complexity of the mathmatical modeling the approach of simplifying basic concepts and focus on practical outcomes by project is very useful. I can't wait to complete the complete program asap. "

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