Ai+ Training

Operationalizing AI Agents in Data Analytics Workflows by Ines Chami

Reinforcement Learning with Human Feedback by Luis Serrano, PhD

“Just Do Something with AI”: Bridging the Business Communication Gap for ML Practitioners by Stephanie Kirmer

Preference Learning from Minimal Human Feedback for Interactive Autonomy by Erdem Bıyık, PhD

Frontiers of Foundation Models for Time Series by Yan Liu, PhD

Towards Deployable Robot Learning Systems by Zipeng Fu

Challenges and Considerations in Language Model Evaluation by Lintang Sutawika

Dimensional Data Modeling in the Modern Era by Dustin Dorsey

AI-Powered ETL Pipeline Orchestration: Multi-Agent Systems in the Era of Generative AI by Brij Kishore Pandey

Small Data Manifesto: Data infrastructure to build bigger with less by Ryan Boyd

Building and Deploying LLM applications with Apache Airflow by Kaxil Naik

Lessons Learned Applying Large Language Models in Healthcare by David Talby, PhD

Explainability Explained: From Beta coefficients to SHAPly Values by Giorgio Francesco Clauser

RAG Pipelines Letting You Down? How The Fitch Group Handles High-Similarity, Frequently Updated Document Sets in Financial Services by Pablo Vega-Behar

Building Reliable Voice Agents with Open Source Tools by Sara Zanzottera

Scaling Deep Learning Training with Fully Sharded Data Parallelism in PyTorch by Shagun Sodhani

Creating APIs That Data Scientists Will Love with FastAPI, SQLAlchemy, and Pydantic by Ryan Day

Using APIs in Data Science Without Breaking Anything by Ryan Day

Introduction to Prompt Engineering and AWS Bedrock for Backend and Data engineers by Elad Hirsch

Building an Agentic Rag Application with LangGraph by Valentina Alto

Topological Deep Learning Made Easy with TopoX by Dr. Mustafa Hajij

Building LLM Applications Using Open-source Models by Sudip Shrestha, PhD