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AI Architecture

AI Architecture

AI Architecture

Welcome to the AI ARCHITECTURE COURSE!

The AI Delivery and Strategy course equips executives, managers, and technical professionals with the knowledge to implement AI effectively within businesses. This intensive program goes beyond the hype, providing a comprehensive foundation in AI principles, frameworks, and best practices.

Participants gain a deep understanding of AI modalities and how to identify suitable business problems for AI solutions. The course delves into training, validating, and deploying AI models, while emphasizing MLOps best practices for monitoring and maintaining them. Governance through an AI Center of Excellence is explored as a way to ensure ethical and compliant AI adoption, considering industry-specific regulations.

With a business-first approach, the course highlights the importance of security, scalability, and performance in AI architectures. Participants gain the skills to communicate AI concepts to both technical and non-technical audiences, fostering collaboration and building consensus. Earning a globally recognized certification and joining a supportive professional community are additional benefits of this program.

Competency Focus Areas

  • Understand what AI tools to use and when
  • How MLOps can be woven in an existing culture of automation
  • Articulate core ML concepts in both orthodox and heterox applications
  • How to monitor AI systems for performance and reliability
  • What security risks and ethical obligations exist for your use cases
  • How the AI Center of Excellence model can be applied to your company to create a hub for AI innovation and discovery
  • Which laws and regulations are relevant to your industry and geography

Who is this course for?

The IASA AI Delivery and Strategy Course is ideal for IT executives, directors, managers, architects, and senior technical practitioners that want to accelerate their company’s ethical and effective AI adoption. These leaders will be confident when taking the best practices and lessons learned in this course directly back to their respective
organizations to have an immediate and palpable impact.

AI Architecture Course
  • CITA-A Certification Included
Next Dates
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What you'll learn

  • Understand what AI tools to use and when
  • How MLOps can be woven in an existing culture of automation
  • Articulate core ML concepts in both orthodox and heterox applications
  • How to monitor AI systems for performance and reliability
  • What security risks and ethical obligations exist for your use cases
  • How the AI Center of Excellence model can be applied to your company to create a hub for AI innovation and discovery
  • Which laws and regulations are relevant to your industry and geography
Module 1

AI Foundation

Lecture Topics

  • Introduction to AI.
  • Impact of AI on our business.
  • Architectural overview.
  • Understanding AI Topics.

Facilitated Peer Discussion

  • Architecture use of patterns.
  • Discuss how the IASA repository matches and can be utilized.
Module 2

AI Foundation

Lecture Topics

  • Selecting a mode.
  • Interacting with Data.
  • Agentic AI introduction.
  • Software Engineering with AI.

Facilitated Peer Discussion

  • Discuss the trade-offs.
  • Discuss what is required with Artificial Intelligence.
  • Discuss using an existing model vs creating your own model.
Module 3

Prompt Engineering 

Lecture Topics

  • Prompt Engineerin.
  • Prompt Framework.
  • Grounding.
  • RAG.

Facilitated Peer Discussion

  • Discuss prompt engineering activities.
  • Discuss the frameworks and how they benefit your interaction with models.
  • Discuss using your own data.
Module 4

AI Software Architecture 

Lecture Topics

  • Describe software architectures to be used with AI.
  • Describe the capabilities of AI.
  • Describe views/viewpoints in AI design.

Facilitated Peer Discussion

  • Discuss AI capabilities and model types.
  • Discuss the skills and knowledge that is needed by the different roles on a team.
  • Discuss the hype cycle and how it impacts the industry.
Module 5

AI Foundation

Lecture Topics

  • Understanding LLMOps.
  • Understanding the LLMOps lifecycle.
  • Describing Evaluations.
  • Walking through monitoring and automation.

Facilitated Peer Discussion

  • Discuss the similarities and differences between DevOps and LLMOps.
  • Discuss the changes that you need to be aware of in the LLMOps lifecycle.
  • Discuss evaluations and why they are needed.
  • Discuss monitoring and automation in your solutions.
Module 6

AI Governance

Lecture Topics

  • Outline AI Governance.
  • Describe governance principles.
  • Describe model governance.
  • Describe Operations governance.

Facilitated Peer Discussion

  • Discussion about creating AI Governance.
  • Discussion on differences of existing governance activities and those required of AI.
  • Discussion operations governance.
  • Discussion of creating your own governance model.
Module 7

Agents and Agentic AI

Lecture Topics

  • Learn the different types of agent AI patterns.
  • Understand how and why Domain Driven Design is so important in Agentic AI.
  • Describe the risks and safeguards required.

Facilitated Peer Discussion

  • Discussion on Agentic AI compared with other AI patterns.
  • Discussion on patterns.
  • Discuss the need and benefits of Domain Driven Design.
  • Discussion on risks and safeguards.
Module 8

Agents and MCP

Lecture Topics

  • Understanding current challenges.
  • Understanding MCP.
  • Understanding limitations with MCP.
  • MCP Security.
  • Understanding AI Gateway services.

Facilitated Peer Discussion

  • Discuss the challenges that brought about the need for MCP.
  • Discussion on performance topics for MCP.
  • Discussion on MCP security.
Module 9

Agents and A2A

Lecture Topics

  • Understanding A2A.
  • Understanding the implementation and use of A2A.
  • Understanding A2A security.

Facilitated Peer Discussion

  • Discuss A2A and where and when to use it.
  • Discussion of differences of A2A and MCP.
  • Discussion on A2A security.
Module 10

Agent Versioning 

Lecture Topics

  • Learn about the agent versioning.
  • Understand what causes versioning activities.
  • Outline agentic behaviors.
  • Understanding versioning strategies.
  • Understand versioning recommendations.

Facilitated Peer Discussion

  • Discuss agent versioning techniques.
  • Discuss what causes versioning events.
  • Discuss agentic behaviors as well as the strategies for versioning.
Module 11

Data Management 

Lecture Topics

  • Understand legacy data challenges.
  • Understanding how to create a trusted data foundation.
  • Understand data estate architecture and transformation.
  • Understand handling structured vs unstructured data.
  • Understand what is required for data readiness.

Facilitated Peer Discussion

  • Discuss challenges surrounding legacy data process and technologies.
  • Discuss data estate architectures and uses.
  • Discuss the topics required for data estate transformations.
  • Discuss trade off and data readiness activities.
Module 12

Quality Attributes

Lecture Topics

  • Presentation of quality attribute topics.
  • Understanding how all of the quality attributes are required for an AI implementation.
  • Understanding of performance and operations requirements/activities.
  • Understanding of the application layer architecture.

Facilitated Peer Discussion

  • Discuss reliability, security, cost optimization, operational excellence and performance topics.
  • Discuss observability and monitoring as well as guidelines for implementation.
Module 13

Case Study  

Lecture Topics

  • Presentation of the case study.
  • Understanding how ML and AI were utilized.
  • Understanding real world privacy in the case study.
  • Review a competitor and the implementation.

Facilitated Peer Discussion

  • How AI was used in both scenarios.
  • Discussion on the technologies and their implementation.
  • How the implementation brings together all of the topics in this course.
Module 14

Final Presentations  

Lecture Topics

  • Present a review of material.
  • Review all the design cards put together by the students.
  • Wrap up and discussion.

Facilitated Peer Discussion

  • Discuss the design implications and impacts in creating an AI solution.
Module 15

Closeout Module 

Lecture Topics

  • Review of the topics that were covered.
  • Discuss the next steps in your learning path.

Facilitated Peer Discussion

  • Final review of the course.
  • Discussion on the interactive activities in the course.

Teaching Modalities

  • 5 days
  • 4 lessons per day
  • Full time
  • 45 min presentation
  • 45 min workshops with. group
  • Classroom
  • Classwork – Miro
  • Course Material – MS Teams
  • 9 weeks
  • 4 hrs per week plus homework Total 6 hrs/wk
  • 45 min lessons
  • 1 hr group work
  • Homework
  • Final presentation to instructor for grade
  • Online (Teams)
  • Homework – Miro
  • Course Material – MS Teams
  • 10 weeks
  • 2 hrs Online Self-Paced
  • 2 hrs Homework
  • 2 hrs Mentor meeting to review homework
  • Final presentation to mentor for grade
  • Online Instructor Reviewed
  • Homework
  • Homework – Miro
  • Course Material – Chronus

Competency Focus Areas

Business architecture is an essential aspect of any organization that aims to improve its operational efficiency, customer satisfaction, and profitability.

Empower Your Career

By the end of this course, students will have developed a deep understanding of business architecture principles and practices.

Our Instructors

Our expert bring real-world experience and cutting-edge knowledge.

Maintaining your IASA certification

Earning your IASA certification is a big achievement—we’re here to help you maintain it. Continuous skill growth that extends beyond certification is critical to fueling your career and your impact. IASA certification holders need to earn

  • Learning
  • Teaching others
  • Presenting
  • Reading
  • Volunteering
  • Content creating
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