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THIS IS PAID EVENT. PRE-REGISTRATION IS REQUIRED. RSVP here - https://lu.ma/lqgq5hi2 Use code CommunityEast2025 for an extra discount.

On its 10th anniversary, ODSC East will feature 250+ speakers, instructors, and practitioners, 2,500 of your fellow data and AI practitioners, and hands-on instruction for world-class experts in:

AI Agents \| Generative AI \| Large Language Models \| AI Engineering \| Machine Learning \| Deep Learning \| MLOps and LLMOps \| AI for Biotech\, Pharma\, and Life Sciences \| Data Engineering \| Data Visualization and Analysis \| and much more.

More details about networking, learnings and schedule you may find here - https://hubs.li/Q02YK3hT0

First confirmed speakers: - Ryan Harter\, Senior Staff Data Scientist at Shopify - Allen Downey\, PhD\, Curriculum Designer \| Professor Emeritus at Brilliant.org \| Olin College - Dr. Jon Krohn\, Chief Data Scientist at Nebula.io - Suman Debnath\, Principal AI/ML Advocate at Amazon Web Services - Andras Zsom\, PhD\, Assistant Professor of the Practice, Director of Graduate Studies at Data Science Institute, Brown University - Rajiv Shah\, PhD\, Machine Learning Engineer at Contextual AI - Peter Henstock\, PhD\, Senior Machine Learning Engineer at Incyte - Noah Giansiracusa\, PhD\, Associate Professor of Mathematics and Data Science at Bentley University - Stella Biderman\, Executive Director\, AI and NLP Researcher \| Lead Scientist - Mathematician at Eleuther AI \| Booz Allen Hamilton - Edward Donner\, Co-founder and CTO at Nebula.io - Chen Wang\, Lead Alliance Solution Architect at AI21 Labs - Sinan Ozdemir\, AI & LLM Expert \| Author \| Founder + CTO at LoopGenius ***- and more - ***https://hubs.li/Q02YK3hT0

🔴 Hands-On Learning: No fluff, no superficial talks – just in-depth workshops, training sessions, and expert-led discussions. 🔴 In-Person Connections: Meet peers, network with industry leaders, and gain actionable insights face-to-face. 🔴 NEW World-Class Venue: Experience it all at the Boston Convention & Exhibition Center, in the heart of the Seaport District.

• “ODSC remains the go-to event for AI and data science practitioners. Complete advanced-level training, engaging and relevant workshops, and exclusive perspectives from thought leaders in the fields.”

– Mansi More \| AI Engineer \| OurDate

• “Open Data Science Conference (ODSC) West 2024 in San Francisco was amazing! So much talent and leadership on display, and really, just a lot of fun.”

– John Ryan Kivela\, MA \| Director of Healthcare Analytics \| Northern Arizona Regional Behavioral Health Alliance ODSC Links:

Useful links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q02ZkDV90 • Code of conduct: https://odsc.com/code-of-conduct/

THIS IS PAID EVENT. PRE-REGISTRATION IS REQUIRED. RSVP here - https://lu.ma/lqgq5hi2 Use code CommunityEast2025 for an extra discount.

On its 10th anniversary, ODSC East will feature 250+ speakers, instructors, and practitioners, 2,500 of your fellow data and AI practitioners, and hands-on instruction for world-class experts in:

AI Agents \| Generative AI \| Large Language Models \| AI Engineering \| Machine Learning \| Deep Learning \| MLOps and LLMOps \| AI for Biotech\, Pharma\, and Life Sciences \| Data Engineering \| Data Visualization and Analysis \| and much more.

More details about networking, learnings and schedule you may find here - https://hubs.li/Q02YK3hT0

First confirmed speakers: - Ryan Harter\, Senior Staff Data Scientist at Shopify - Allen Downey\, PhD\, Curriculum Designer \| Professor Emeritus at Brilliant.org \| Olin College - Dr. Jon Krohn\, Chief Data Scientist at Nebula.io - Suman Debnath\, Principal AI/ML Advocate at Amazon Web Services - Andras Zsom\, PhD\, Assistant Professor of the Practice, Director of Graduate Studies at Data Science Institute, Brown University - Rajiv Shah\, PhD\, Machine Learning Engineer at Contextual AI - Peter Henstock\, PhD\, Senior Machine Learning Engineer at Incyte - Noah Giansiracusa\, PhD\, Associate Professor of Mathematics and Data Science at Bentley University - Stella Biderman\, Executive Director\, AI and NLP Researcher \| Lead Scientist - Mathematician at Eleuther AI \| Booz Allen Hamilton - Edward Donner\, Co-founder and CTO at Nebula.io - Chen Wang\, Lead Alliance Solution Architect at AI21 Labs - Sinan Ozdemir\, AI & LLM Expert \| Author \| Founder + CTO at LoopGenius ***- and more - ***https://hubs.li/Q02YK3hT0

🔴 Hands-On Learning: No fluff, no superficial talks – just in-depth workshops, training sessions, and expert-led discussions. 🔴 In-Person Connections: Meet peers, network with industry leaders, and gain actionable insights face-to-face. 🔴 NEW World-Class Venue: Experience it all at the Boston Convention & Exhibition Center, in the heart of the Seaport District.

• “ODSC remains the go-to event for AI and data science practitioners. Complete advanced-level training, engaging and relevant workshops, and exclusive perspectives from thought leaders in the fields.”

– Mansi More \| AI Engineer \| OurDate

• “Open Data Science Conference (ODSC) West 2024 in San Francisco was amazing! So much talent and leadership on display, and really, just a lot of fun.”

– John Ryan Kivela\, MA \| Director of Healthcare Analytics \| Northern Arizona Regional Behavioral Health Alliance ODSC Links:

Useful links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q02ZkDV90 • Code of conduct: https://odsc.com/code-of-conduct/

When you know the cause of an event, you can affect its outcome. This accessible introduction to causal inference shows you how to determine causality and estimate effects using statistics and machine learning. A/B tests or randomized controlled trials are expensive and often unfeasible in a business environment. Causal Inference for Data Science reveals the techniques and methodologies you can use to identify causes from data, even when no experiment or test has been performed. In Causal Inference for Data Science you will learn how to: Model reality using causal graphs Estimate causal effects using statistical and machine learning techniques Determine when to use A/B tests, causal inference, and machine learning Explain and assess objectives, assumptions, risks, and limitations Determine if you have enough variables for your analysis It’s possible to predict events without knowing what causes them. Understanding causality allows you both to make data-driven predictions and also intervene to affect the outcomes. Causal Inference for Data Science shows you how to build data science tools that can identify the root cause of trends and events. You’ll learn how to interpret historical data, understand customer behaviors, and empower management to apply optimal decisions. About the Technology Why did you get a particular result? What would have lead to a different outcome? These are the essential questions of causal inference. This powerful methodology improves your decisions by connecting cause and effect—even when you can’t run experiments, A/B tests, or expensive controlled trials. About the Book Causal Inference for Data Science introduces techniques to apply causal reasoning to ordinary business scenarios. And with this clearly-written, practical guide, you won’t need advanced statistics or high-level math to put causal inference into practice! By applying a simple approach based on Directed Acyclic Graphs (DAGs), you’ll learn to assess advertising performance, pick productive health treatments, deliver effective product pricing, and more. What's Inside When to use A/B tests, causal inference, and ML Assess objectives, assumptions, risks, and limitations Apply causal inference to real business data About the Reader For data scientists, ML engineers, and statisticians. About the Author Aleix Ruiz de Villa Robert is a data scientist with a PhD in mathematical analysis from the Universitat Autònoma de Barcelona. Quotes With intuitive explanations, application-focused insights, and real-world examples, this book offers immense practical value. - Philipp Bach, Maintainer of the DoubleML libraries for Python and R An essential guide for navigating the complexities of real-world data analysis. - Adi Shavit, SWAPP A must-read! Demystifies causal inference with a blend of theory and practice. - Karan Gupta, SunPower Corporation Causal relationships can mask and distort results. This book provides a set of tools to extract insights correctly. - Peter V. Henstock, Harvard Extension