AIGov‑MLSecOps Conference: Securing and Governing the AI Lifecycle

AIGov‑MLSecOps Conference: Securing and Governing the AI Lifecycle

Learn how to secure and manage AI projects from start to finish at the AIGov‑MLSecOps Conference!

By PLEYVERSE AI

Select date and time

Friday, June 13 · 8am - 4pm CDT

Location

2450 Holcombe Blvd

2450 Holcombe Boulevard Houston, TX 77021

Refund Policy

Refunds up to 7 days before event

Agenda

Day 1
Day 2

8:00 AM - 8:15 AM

Welcome and Introduction - Opening remarks and conference objectives

8:15 AM - 9:00 AM

MLSecOps Essentials - Overview of MLSecOps, Threats, and ML Lifecycle

9:00 AM - 9:45 AM

Introduction to AI Governance - Ethics, accountability, transparency

10:00 AM - 11:00 AM

Data Security Best Practices - Privacy, compliance, secure handling, etc.

11:05 AM - 12:00 PM

Data Governance & Responsible Data Management - Bias mitigation, stewardship

12:00 PM - 1:00 PM

Lunch Break

1:05 PM - 1:50 PM

Case Studies – Real-World Incidents - In-depth cases, group discussion

2:00 PM - 2:45 PM

Real-World Governance Challenges - In-depth cases, group discussion

2:05 PM - 3:50 PM

AI Governance Deep Dive - Ethics, regulatory compliance (panel/workshop)

3:50 PM - 4:00 PM

Q&A and Closing Remarks Day One.

About this event

Conference Overview

The first AIGov‑MLSecOps Conference: Securing and Governing the AI Lifecycle is a pioneering two-day event designed to bridge the gap between cutting-edge machine learning security operations (MLSecOps) and robust AI governance. This conference brings together technical experts and thought leaders to address both the operational challenges of securing AI systems and the ethical, regulatory, and accountability frameworks necessary for responsible AI deployment.

Key Highlights

  • Integrated Approach:
    Explore how MLSecOps—focused on protecting data, models, and ML pipelines—can be seamlessly integrated with AI governance strategies that promote transparency, fairness, and regulatory compliance.
  • Comprehensive Sessions:
    The conference spans foundational sessions on data security and governance, technical deep dives into model and pipeline security, and interactive workshops that invite participants to collaborate on actionable strategies for the future.
  • Expert Speakers:
    Hear from a diverse lineup of experts in machine learning, security engineering, DevOps, and AI governance. Each session is led by specialists who bring real-world insights and practical experience to the forefront.
  • Interactive Learning:
    With a mix of lectures, hands-on demos, case studies, and panel discussions, attendees will gain actionable knowledge and practical tools to navigate both the technical and ethical dimensions of AI system management.
  • Networking Opportunities:
    Engage with peers, industry leaders, and innovators during dedicated networking sessions designed to foster collaboration and share best practices across disciplines.

Who Should Attend

This conference is ideal for:

  • Data Scientists and Machine Learning Engineers seeking to secure and optimize their AI models.
  • Security Engineers and DevOps professionals focused on integrating robust security measures into AI workflows.
  • Compliance Officers, Ethics Experts, and AI Governance Leaders dedicated to ensuring that AI technologies are developed and deployed responsibly.

Conference Goals

  • Enhance Security:
    Equip participants with the latest strategies to protect AI systems against threats such as data poisoning, adversarial attacks, and model theft.
  • Promote Responsible AI:
    Illuminate the importance of ethical considerations and regulatory frameworks in AI development, ensuring that governance is an integral part of the AI lifecycle.
  • Foster Collaboration:
    Create a platform for cross-disciplinary dialogue, enabling professionals from technical and governance backgrounds to work together towards a secure and accountable AI future.

Join us for an immersive experience that not only deepens your technical expertise but also broadens your understanding of the governance frameworks essential to building trustworthy AI systems.

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$308.67