• 1 Hour

  • 4.7/5

  • Intermediate

GenAI Applied to Quantitative Finance: For Control Implementation

This course explores the application of Generative AI in quantitative finance, focusing on building sustainable trading algorithms through keyword extraction, sentiment analysis, and time-series forecasting. Learn to predict commodity prices, such as gold, by integrating data from financial news sources, leveraging sentiment analysis, and optimizing models for robust trading signals.

Course curriculum

  • 1
    Gen AI Applied to Quantitative Finance
    • Introduction
    • Overview
    • Problem Definition: Commodity Price Prediction
    • Architecture
    • Hands-On

Certificate of Completion

Unlock a lifetime-valid certificate from Analytics Vidhya upon completing the course—your achievement is forever recognized!
Certificate of Completion

Who Should Enroll:

This course is ideal for finance professionals, quantitative analysts, data scientists, and traders looking to leverage AI for advanced financial modeling and decision-making. It's also perfect for technology enthusiasts and students eager to explore the intersection of AI and finance, enhancing their skills in algorithmic trading, risk management, and predictive analytics.

Instructor

Sidharth Kumar, Principal Data Scientist at Intuit

Sidharth Kumar, Principal Data Scientist at Intuit, Bangalore, drives AI integration into products like QuickBooks and TurboTax. He has led data science at Flipkart, and worked as a Quant at ACR Capital and Goldman Sachs. He holds a PhD in Astrophysics from the University of Maryland and a Bachelor's from IIT-Madras.
LinkedIn
Instructor

Frequently Asked Questions (FAQs)

  1. What real-world applications are covered?
    You’ll explore AI in trading, risk management, and portfolio optimization, with practical examples of AI-driven finance solutions.

  2. Is there hands-on experience with AI tools?
    Yes, you'll work with Python-based AI tools and machine learning techniques directly applied to finance problems.

  3. How does the course address control implementation?
    The course teaches how to implement and maintain reliable AI models, focusing on risk mitigation and performance optimization.

  4. What projects or assessments are involved?
    You'll design trading algorithms, test risk models, and apply GenAI techniques to real-world financial challenges.

  5. How will this course benefit my career?
    You’ll gain cutting-edge AI skills in finance, positioning you for roles like quant analyst, data scientist, or AI strategist.

Key Takeaways from this Course

  • Learn how to apply advanced AI techniques to convert textual data, such as news articles, into actionable trading signals for predicting commodity prices.

  • Understand the importance of a well-structured architecture that includes robust keyword extraction, sentiment mining, graph generation, and time series forecasting to drive predictive accuracy.

  • Explore opportunities for further improvements, such as integrating large language models (LLMs), enhancing robustness, and achieving full automation in trading signal generation.