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Foundations of AI-Ready Enterprise Architecture

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Packt

Foundations of AI-Ready Enterprise Architecture

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Design AI-ready data architectures that scale in production

  • Implement governance and compliance frameworks for AI

  • Apply real-world AI solutions across multiple industries

Details to know

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Recently updated!

September 2026

Assessments

6 assignments

Taught in English

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This course is part of the Architectures for the Intelligent AI-Ready Enterprise Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 5 modules in this course

This module provides an in-depth look at the strategic differences between AI modernization and innovation, helping learners navigate the challenges of AI implementation and avoid common pitfalls. It explores how organizations can build a strong foundation for AI adoption and align innovation with sustainable practices. Learners will gain insights into planning and executing AI strategies effectively.

What's included

1 video4 readings1 assignment

This module provides an in-depth look at the differences between Generative AI, RAG, and Agentic AI, focusing on how each system processes data, generates content, and applies knowledge. Learners will gain an understanding of foundational AI technologies and their practical implementations in real-world scenarios.

What's included

1 video9 readings1 assignment

This module explores the key components of system design for real-time AI, including data access, integration, and governance. Learners will gain insights into how enterprises can build robust GenAI solutions that support business outcomes while addressing security and compliance challenges. The content covers practical strategies for handling multimodal data and ensuring data quality.

What's included

1 video5 readings1 assignment

This module explores the key principles of trustworthy AI, regulatory compliance, and data governance. Learners will gain insights into how ethical frameworks, stakeholder engagement, and data practices contribute to building responsible AI systems. The module also covers real-world applications and challenges in implementing these concepts across industries.

What's included

1 video6 readings1 assignment

This module explores strategies for modernizing legacy systems using AI, focusing on overcoming technical limitations, automating workflows, and leveraging AI for code transformation and deployment. Learners will gain insights into how AI can streamline processes, reduce risks, and drive innovation in system upgrades.

What's included

1 video7 readings2 assignments

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Instructor

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Packt
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