AI Con USA 2025 - Data Scientist
Customize your AI Con USA 2025 experience with sessions for data scientists.
Monday, June 9
Beginning Data Analysis and Machine Learning with Jupyter Notebooks
In this beginner-friendly workshop you'll see how you can get started with data analytics and data science using Jupyter Notebooks. Matt will start with the basics of notebooks and then move on to using Python, Pandas, and NumPy to perform basic exploratory data analysis. See how you can use Plotly Express to create interactive charts and visuals with only a minimal amount of code. Once you've grasped the basics of understanding and visualizing the data Matt will move on to machine learning with SciKit-Learn as you train and evaluate predictive regression and classification models. The...
Get Your Data Ready for AI/ML
Understanding the readiness of your source data before you launch an expensive AI/ML project lets you take corrective data engineering measures that will streamline the project and give you the best probability of a successful outcome. Artificial Intelligence (AI) and Machine Learning (ML) projects can provide significant returns on investment when they are applied to narrow but difficult business problems and are supported by adequate amounts of relevant, quality data. Many such projects start with high hopes but get derailed due to fundamental problems with source data, which were...
Tuesday, June 10
AI Deep Dive: Exploring AWS Using Real-World Scenarios
Deepen your AI and machine learning expertise using AWS in an Immersive, hands-on workshop. You’ll use real-world AI challenges while leveraging AWS services like Amazon SageMaker, Bedrock, and Lambda to build and optimize AI-driven solutions. As the session unfolds, new constraints and data anomalies will emerge, mirroring the complexities of real-world AI/ML implementation. Gain insight into how AI solutions perform under evolving conditions, learning to adapt, optimize, and troubleshoot unexpected challenges. Learn the importance of collaboration, strategic thinking, problem-solving,...
Wednesday, June 11
Test Machina: Demystifying AI-Driven Testing Agents
Software vendors and practitioners are using artificial intelligence (AI) and machine learning (ML) to create a new wave of test automation tools. Such tools leverage autonomous and intelligent agents to explore, model, reason and learn about a software product. But how do these testing agents really work? Is this technology any good? And can we really trust them to validate software? Tariq King will introduce you to the world of agentic AI and discuss its benefits, challenges and other limitations. Learn how AI test agents use AI/ML technologies to mimic human testing activities such as...
Powering Complex Solutions with Agentic Systems
This session explores the revolutionary potential of agentic systems—autonomous agents equipped with diverse tools to tackle multifaceted tasks effectively. By integrating tools, agentic workflows enable intelligent, adaptive solutions to complex challenges. Apurva will start with an introduction to agentic systems, highlighting their ability to utilize various tools dynamically to achieve goals with minimal human intervention. Through real-world case studies, she will demonstrate how tools like APIs, databases, and external services are orchestrated within these systems to simulate...
Securing the Foundations of AI: Addressing the Past to Safeguard the Future
AI’s future hinges on an ecosystem built on decades of technical debt, fragmented tools, and opaque processes; creating vulnerabilities that threaten the reliability and security of modern applications. In this talk, Peter will examine how the legacy of open-source numerical computing and software supply chains is influencing AI’s trajectory. Drawing from over a decade of leadership in the Python and scientific computing communities, Peter will share strategies for tackling these challenges: improving transparency in data and dependencies, building curated software stacks, addressing...
Thursday, June 12
RAG at Scale: Building Production-Ready GenAI Solutions
This session serves as a deep dive into the strategies and best practices for data scientists aiming to build, fine-tune, and scale Retrieval Augmented Generation (RAG) based Generative AI (GenAI) applications. The core objectives for data scientists in the AI development cycle center around providing highly relevant results for end users and maintaining cost-effectiveness to support the sustainable growth of their products. RAG is a pivotal method that enables GenAI applications to operate effectively on proprietary data. At the heart of RAG are robust retrieval systems, which are crucial...
RAG Has Evolved - Enhance Your RAG Pipeline with These Concepts
The majority of businesses today can set up a fundamental RAG pipeline that effectively handles most use cases. However, this basic setup eventually reaches its limitations in terms of functionality and accuracy, hindering further advancements. Matt Payne aims to detail the necessary pipeline components for building advanced RAG pipelines. For each component, he will explain the what, when, why, and how and provide real-world examples. Key areas of focus include leveraging tools and function calling, which enables you to create a systematic approach to using knowledge from multiple sources...
Navigating Compliance with the EU AI Act: Strategies for Responsible AI Development and Governance
As AI systems continue to transform industries, the EU AI Act sets a pivotal regulatory framework to ensure responsible and ethical use of artificial intelligence across Europe. This session will provide practical insights into navigating compliance with the EU AI Act, addressing key requirements for high-risk AI systems, transparency, accountability, and data governance. Joanna will explore how organizations can align their AI development processes with the Act's standards while maintaining innovation. Attendees will gain actionable strategies for integrating compliance into existing...