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Course curriculum

  • 1

    ODSC West Keynotes

    • The Current and Future State of Autonomous Agents by Yohei Nakajima

    • Beyond Models – Applying AI and Data Science Effectively by Dr. Alfred Spector

    • Virtual Fireside Chat with Gary Marcus, PhD

  • 2

    ODSC West Bootcamp

    • A Practical Introduction to Data Visualization for Data Scientists by Robert Kosara

    • Introduction to Machine Learning with Python by Sudip Shrestha

    • Statistics and Hypothesis Testing by Thomas Nield

    • Introduction to Retrieval-Augmented Generation (RAG) by Sheamus McGovern

  • 3

    ODSC West Talks

    • 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

  • 4

    ODSC West Tutorials and Training

    • 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 Containers for Data Science / Data Engineering by Michael A Fudge

    • A Gentle Introduction to Vector Databases and Their Implementation by Balaji Dhamodharan

    • LLMOps Infrastructure for Production-grade RAG Applications by Niels Bantilan

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

    • Building a Multimodal AI Assistant: Build an AI Application Using Advanced RAG for Cross-Modal Data Retrieval by Suman Debnath

    • 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

    • Building Agentic and Multi-Agent Systems with LangGraph by Greg Loughnane and Chris Alexiuk