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AI Engineering Accelerator - 9 Jun - 23 Jul

6-Week | 8-Course AI Accelerator | Virtual

Begin your accelerator journey with Live and on-demand training to build confidence in the fundamentals. Steadily progress through the Accelerator week with our hands-on training and expert-led sessions and workshops.

Why you start here: Build your unshakeable core. This phase guarantees success, ensuring you confidently grasp essential AI concepts and tools, from basic literacy to advanced AI building blocks.

What you gain: Master AI/Data Literacy, Python, Data Wrangling, Generative AI fundamentals, LLMs, RAG, and the crucial progression to AI Agents, plus Machine Learning basics, through 8 live virtual courses and on-demand training. Gain foundational fluency to accelerate your entire AI journey.

8 VIRTUAL LIVE TRAINING | SESSIONS LENGTH: 2.5 HOURS

6-Week AI Engineering Accelerator

Course of the Week

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Talk

The Cognitive Switch: Engineering Embodied AI

Embodiment changes how humans interact with technology. When AI projects presence through voice or avatars, our brains instinctively apply real-world social rules, fundamentally shifting user trust and behavior.

This keynote explores the intersection of cognitive science and system architecture. Discover why embodiment alters human cognition, evaluate the engineering trade-offs of real-time multimodal systems, and watch a live technical build of voice and avatar agents using open-source tools. You will leave with a practical framework to safely decide when – and how – to bring your AI into the physical or visual world.

Embodied AI: A Cognitive Shift, Not a Cosmetic Change

Video of the Month

Featuring 7-Week AI Accelerator Sessions, Agentic AI Summit + MORE

Counterfactual Analysis with Bayesian Models: What Drives the Life Expectancy Gap?

with Allen Downey, PhD, Principal Data Scientist at PyMC Labs

In this talk, I present a practical approach to counterfactual analysis using Bayesian regression models.

The model generates posterior simulations that answer “what-if” questions.

The talk presents the workflow from assembling global datasets to fitting interpretable Bayesian models with PyMC and generating counterfactual simulations. Attendees will learn how Bayesian models can support explainable modeling and analysis under uncertainty.

The Data Scientist’s New Mandate: Why AI Governance is Now Part of the Job

https://opendatascience.com/

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