How to survive building AI systems when things change every week

On-Device AI: Privacy, Performance, and Real-World Edge Systems

Recent Advances in the Design and Analysis of Network Experiments

From Models to Impact: Applying LLMs to Solve Business Problems

The Impact of AI on Data Science Development

From Word2Vec to GPT: How AI Learns Language and How We Evaluate Them

Building the Intelligence Platform for the Future of Vehicle Payments

Building Intelligent Agents with the AWS Generative AI Ecosystem

Real-time AI for high-speed decisioning & hyper-personalization by Srini V Srinivasan

The Next Frontier of Data Science At The Edge by George Williams

Data Science at the frontier - A Startup Founder's Journey by Pratyush Tiwari

Running Models Where Your Users Are by David Aronchick

Encoder-Only Transformers, the unsung heroes of the AI revolution by Josh Starmer

Revolutionizing Retail: Vision-Language AI for Style Filters & Attribution

Beyond the Resume: Traits That Set Top Data Scientists Apart

The Versatile Data Scientist: Adapting to Diverse Roles on Small Teams

Unstructured Data Analytics unlocked by Multimodal LLMs

Applications and challenges of ML/AI in Healthcare

Solving Natural Language Processing Tasks with the Hugging Face API

DIY LLMs: Hosting your own LLM inference, from silicon to service

Oh the places you might go! (as a data professional)

Evolution of data science in the era of GenAI

Navigating the Vehicle Data Landscape - From Robots and Planes to Payments

Establishing Your "Data Culture" in Early-Stage Startups

Can ads be a good thing? A deep look into the tech that moves people to action

Embed Your Impact in Every Line of Code: Use Data to Save the Earth

Let Robots Do the Hard Work: Data Governance in the Age of AI

Low-Rank Adaptation: Exploring LORA for Efficient Language Model Fine-Tuning

Security and Governance for Generative AI Applications

MultiModal LLM: Merging categorical & continuous features using DistilBERT

Recruiter Panel: Technical Sessions

Image Segmentation with PyTorch

How to get a data science job: Strategies that actually work

Solving Natural Language Processing tasks with the Huggingface API

Mark Saroufim: Machine Learning has become Necromancy

Nicolas Thiebaut: Language Agents – Large Models to Autonomous Systems

Beinan Wang: Data Access Patterns in AI and Analytics

Pratima Satish: A Deep Dive into Machine Learning

An environmental cost-effectiveness analysis of methods for performing colon cancer screening

Pardhu and Prithvi: Smart Metadata: AI's Impact on Modernizing Data Catalogs

Jared & Archana: Trends in Risk Management - Evolving Audit & Advisory with Data

Melanie Palmer: Leveraging Data for Real-Time Event Support

Vinay Sankarapu: ML Observability for High-Risk AI Governance Framework

Nick Singh: Ace the Data Science Interview

Jay Feng: Acing the Data Science Interview with Interview Query

Plenary with DJ Patil, Former U.S. Chief Data Scientist

Uday Marepalli: Concept to Launch, Building Machine Learning Products

Funmi Doro, How to avoid surprising outcomes after models are deployed to production.

Mars Lan, Co-Founder & CTO at Metaphor Data: Metadata Is the New Refinery

Cameron Carlin: Applied AI and Data Science at City of Hope

Bin Fan, Founding Member and VP of open source, Alluxio

Data Institute: Sachin Pendse, From Treatment to Healing

MS in Data Science Seminar Series: Jennifer Zhu, Amazon AI

Minha Hwang, Principal Architect @Microsoft: Data-centric Causal Modeling of Promotion Effectiveness

Victor Palacios & Corey Weisinger, KNIME: (Codeless) Data Science Interviews

Julien Penders, Co-Founder @Bloomlife: Improving Prenatal Health w/ Large Scale Data Analysis

Erin LeDell, Chief Learning Machine Scientist at H2O.ai: Admissible Machine Learning

Timnit Gebru: Distributed Artificial Intelligence Research Institute (DAIR)

Nick Ross, Director DS/Backend Engineering, The Meta: A/B Testing Incorrectly

Newsha K. Ajami: Harnessing the Digital Revolution to Assess Water Use Dynamic