Enterprise AI Integration (EAII)

 

Course Overview

This course guides business leaders and technical strategists through the integration of AI into enterprise ecosystems. It covers the foundations of enterprise AI, the Google Cloud AI ecosystem including Gemini and Vertex AI, and essential integration patterns like data flow and event-driven architectures. The training also outlines a seven-step implementation strategy, governance frameworks, and methods for managing organizational change to ensure successful AI adoption.

Who should attend

Business leaders with some technical knowledge.

Prerequisites

There are no specific prerequisites for this course, though a basic understanding of cloud computing concepts is beneficial.

Course Objectives

  • Map Google Cloud AI tools to high-value use cases.
  • Design basic AI integration patterns.
  • Develop an AI implementation roadmap.

Outline: Enterprise AI Integration (EAII)

Module 1 - Foundations of enterprise AI

Topics:

  • The enterprise AI integration imperative
  • What do we mean by 'enterprise AI'?
  • Agentic AI and capabilities of agents

Objectives:

  • N/A

Activities:

  • N/A

Module 2 - Google Cloud enterprise AI ecosystem

Topics:

  • The Google Cloud AI advantage
  • The foundation layer: Gemini models and capabilities
  • The application layer: Daily tools and research assistance
  • The customization layer: Vertex AI Agent Builder
  • The trust layer: Security and governance

Objectives:

  • Map Google Cloud AI tools to high-value use cases.

Activities:

  • 5x demos

Module 3 - Enterprise AI integration patterns

Topics:

  • Integration strategy and unified interface
  • Integration patterns
  • API strategy
  • Integration security and governance

Objectives:

  • Design basic AI integration patterns.

Activities:

  • N/A

Module 4 - Enterprise AI implementation

Topics:

  • Steps to build an enterprise AI integration strategy
  • Defining business goals and identifying high-impact use cases
  • Assessing data readiness and choosing technology
  • Establishing governance and developing AI
  • Managing organizational change and building an AI culture

Objectives:

  • Map Google Cloud AI tools to high-value use cases.
  • Develop an AI implementation roadmap.

Activities:

  • N/A

Module 5 - Summary and quiz

Topics:

  • Summary of key concepts

Objectives:

  • Review key learnings and assess knowledge retention.

Activities:

  • 1x quiz (3 questions)

Module 6 - Appendix

Topics:

  • Cymbal companies overview
  • Industry spotlight: Agent capabilities
  • Industry spotlight: Integration patterns

Objectives:

  • N/A

Activities:

  • N/A

Prices & Delivery methods

Online Training

Duration
3 hours

Price
  • CAD 485
Classroom Training

Duration
3 hours

Price
  • Canada: CAD 485

Schedule

Currently there are no training dates scheduled for this course.