Announcing the First Sessions for ODSC Europe 2024 Announcing the First Sessions for ODSC Europe 2024
ODSC Europe is still a few months away, coming this September 5th-6th, but we couldn’t be more excited to announce our... Announcing the First Sessions for ODSC Europe 2024

ODSC Europe is still a few months away, coming this September 5th-6th, but we couldn’t be more excited to announce our first group of sessions. Our expert speakers will cover a wide range of topics, tools, and techniques that data scientists of all levels can apply in their work. Check a few of them out below.

First ODSC Europe 2024 Sessions

Reinforcement Learning for Finance

Dr. Yves J. Hilpisch, CEO | The Python Quants & The AI Machine | Adjunct Professor of Computational Finance

Reinforcement learning and related algorithms, such as Deep Q-Learning (DQL), have led to major breakthroughs in different fields. DQL, for example, is at the core of the AIs developed by DeepMind that achieved superhuman levels in such complex games as Chess, Shogi, and Go (“AlphaGo”, “AlphaZero”). Reinforcement Learning can also be beneficially applied to typical problems in finance, such as algorithmic trading, dynamic hedging of options, or dynamic asset allocation. The workshop addresses the problem of limited data availability in finance and solutions to it, such as synthetic data generation through GANs.

Data Morph: A Cautionary Tale of Summary Statistics

Stefanie Molin | Data Scientist, Software Engineer, Author of Hands-On Data Analysis with Pandas | Bloomberg

Statistics do not come intuitively to humans; they always try to find simple ways to describe complex things. Given a complex dataset, they may feel tempted to use simple summary statistics like the mean, median, or standard deviation to describe it. However, these numbers are not a replacement for visualizing the distribution.

 In this talk, Stefanie will discuss Data Morph, an open source package that builds on previous research from Autodesk (the Datasaurus Dozen) using simulated annealing to perturb an arbitrary input dataset into a variety of shapes, while preserving the mean, standard deviation, and correlation to multiple decimal points. The speaker will showcase how it works, discuss the challenges faced during development, and explore the limitations of this approach.

Generative AI: The Supply Chain Alchemist, Turning Data into Superhuman Business Insights

Denis Rothman | Generative AI, Public Speaker, Instructor, Author | Rothman-AI

In this talk, we’ll dive into the real-world applications of Generative AI, from hyper-accurate demand forecasting to dynamic logistics optimization and proactive risk mitigation. We’ll explore how this cutting-edge technology is slashing costs, boosting revenues, and enhancing agility for businesses across industries.

Using concrete examples in code, we’ll demonstrate how Generative AI can tackle everyday challenges. We will focus on unexpected equipment and service failures leading to customer support. You will learn how to turn vast amounts of data into actionable insights that drive smarter decision-making and tangible results.

Building Reliable Voice Agents with Open-Source Tools

Sara Zanzottera | AI Engineer | Kwal

Large Language Models (LLMs) are great at writing. Behind a chat interface, they can chat with users almost like a real human would. But are they able to talk like a human? Voice Agents are LLM-powered applications that can listen to users and talk back to them with a realistic voice, handle interruptions, and improvise while sticking to the goal they’re given. 

In this session, we will learn how they’re made, which open-source tools are available to build them, and we are going to see in practice how to build one. Along the way, we will see what’s their industry impact today and what are the challenges of bringing a voice agent PoC to production, with some real-world stories from our own journey from a small demo to a large-scale deployment.

Designing AI Architectures with Domain-Driven Design: A Use Case-Centric Approach

Shawn Kyzer | Associate Director, Data Engineering, Research & Early Science | AstraZeneca

In the rapidly evolving landscape of artificial intelligence, designing architectures that effectively align with business objectives and deliver lasting value remains a critical challenge. This talk presents a fresh perspective on tackling this challenge by leveraging the power of Domain-Driven Design (DDD) in the context of AI system development.

Through a use case-centric approach, we will explore how DDD principles can be applied to create modular, scalable, and maintainable AI architectures. We will delve into key concepts such as bounded contexts, microservices, and tactical patterns, and demonstrate their practical application in designing AI systems.

How to Run Scalable, Fault-Tolerant RAG with a Vector Database

JP Hwang | Technical Curriculum Developer | Weaviate

Prototyping retrieval augmented generation (RAG) apps can be easy with modern generative AI tools and frameworks. But the journey from prototyping to production is anything but easy with many traps and pitfalls. In this workshop, you’ll get to see first-hand some of the potential risks, and how the right infrastructure tool can help you to mitigate them.

During the workshop, you will implement features like quantization, multi-tenancy, replication, and horizontal scaling. In turn, you will experience how big a difference each of these can make to the RAG system’s performance.

Optimizing GenAI Outcomes in Financial Services with DSPy

Alberto Romero | Director, GenAI Platform Engineering | Citi

As the financial services industry embraces GenAI to drive innovation and efficiency, the need for robust and trustworthy outcomes becomes paramount. Traditional RAG pipelines, while powerful, often fall short in addressing the unique challenges of the finance domain, such as data and model interpretability. 

This talk delves into the architectural advantages of DSPy over traditional RAG pipelines, highlighting its ability to optimize prompt instructions, enable fine-grained optimization, and facilitate interpretable decision-making processes. Through real-world use cases and code examples, we will explore how DSPy’s unique features, such as signature-based programming, chained LLM calls, and optimization techniques, can unlock new frontiers in GenAI adoption across financial services.

Register for ODSC Europe today

And that’s just the start! We’ll be adding more sessions as we get closer to the conference, so be sure to keep an eye out. And remember to get your pass soon. Our limited-time offer of 70% off any ODSC Europe in-person or virtual pass won’t last forever.



ODSC gathers the attendees, presenters, and companies that are shaping the present and future of data science and AI. ODSC hosts one of the largest gatherings of professional data scientists with major conferences in USA, Europe, and Asia.