Guided by Nicole Königstein, a renowned professor and expert in AI research
Nicole Königstein
Just a few reasons why this course is awesome:
Your guide is Nicole Koenigstein, an AI expert who knows all about trading and making smart strategies. She's here to make it easy to understand and fun to learn!
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Learn from the best
This course is all about hands-on learning! You’ll work on real tasks, play around with tools like Jupyter notebooks, and actually use what you learn right away.
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Learn by doing
Discover how to apply LLMs and AI agents to trading — and be among the first to gain this game-changing skill.
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Get a head start
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This course skips the boring theory and focuses on hands-on skills to help you use AI tools for trading. Be the trader who’s ahead of the game and shaping the future of finance!
Master the skills of tomorrow's trading
AI is transforming the trading world, especially with tools like Large Language Models (LLMs) that are revolutionizing algorithmic trading.
Here’s why LLMs are critical for the future of trading
The integration of AI and NLP models, including LLMs, has been shown to improve trading performance by up to 15%. This is due to more accurate analysis of market sentiment and real-time decision-making.
AI tools can analyze earnings reports, news articles, and financial documents at a speed and accuracy unmatched by traditional methods, reducing research time by up to 50%.
Nicole brings years of expertise in AI-driven trading, quantitative finance, and data science to this course. Her hands-on approach will ensure you not only understand LLMs but can also apply them effectively in real trading environments.
Nicole Königstein
Chief AI Officer & Head of Quantitative Research at Quantmate
This course is focused on practical knowledge that you can start applying immediately to your trading strategies. We cover nothing extra — only the essentials you need to succeed.
Here’s what you’ll learn
Curriculum:
Intro to LLMs in future markets and algorithmic trading
Webinar №1
Role of LLMs in AI-driven trading
Looking ahead: the future of LLMs in trading
Introduction to large language models (LLMs)
Theoretical foundations of LLMs
Research and frameworks
Practical applications in trading
LLMs in action: practical applications for futures markets and algorithmic trading
Webinar №2
Developing data-driven solutions
Hands-on understanding of LLM integratio
Actionable workflows for LLM implementation
Strategies for automating complex processes
Streamlining tasks with LLMs
Enhancing decision-making with LLM agents
Boosting efficiency in real-world settings
Introduction to LLMs
Tokenization and embeddings
Application of LLMs to financial markets and algorithmic trading
Overview of transformer architecture and attention mechanisms
Advanced techniques
Benefits of quantization in LLMs
Prompt engineering techniques: such as zero-shot, few-shot, chain-of-thought, tree of thought
What is fine-tuning?
Parameter-efficient fine-tuning (PEFT) and low-rank adaptation methods
What is quantization?
What is sharding?
How sharding optimizes LLM performance
Retrieval-augmented generation (RAG)
Introduction to retrieval-augmented generation
Using RAG for financial report summarization and real-time market updates
Advanced techniques: Corrective RAG and Graph-based RAG for more accurate information
Practical application
Summarizing financial reports and extracting actionable insights
Identifying companies with LLM
LLMs for sentiment analysis of news and financial reports
Identifying market sentiment shifts to inform trading decisions
Incorporating sentiment data into algorithmic trading models
Name-entity recognition
Financial relation construction
LLM agents
Intro to agents
One-step, multi-step and other agent architectures
Designing and implementing an algorithmic trading bot using LLM agents
Multi-agent systems for real-time decision-making
Responsible LLMs
Tools for maintaining AI transparency and explainability
Create and improve bots that adapt and trade in real-time.
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Build smart trading bots
Use AI tools to do research and analysis faster and smarter.
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Save time with AI
Learn how to use data and insights to make better trading decisions.
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Trade more accurately
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Earn an official certificate
Earn a verified certificate upon course completion to showcase your expertise, boost your LinkedIn profile, and unlock career opportunities in trading and fintech.
💎 Webinar-only deal
Exclusive for webinar participants
$250
$850
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Exclusive employment & networking opportunities
Get our premium program for just $250 and unlock:
Two bonus courses on quantitative trading with mentorship support
24/7 human support
Course on automating trading strategies using LLMs and AI
Act fast — this offer is only available until January 18th!