Online Course
Building Your AI Ecosystem: Technology, Infrastructure, and Partnerships

Learn how to build an adaptable AI tech stack, connect AI with existing business systems, and choose infrastructure that fits your organization’s needs.

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  • Institute of Analytics
  • E-Learning Quality Network
  • European Agency for Higher Education and Accreditation
  • Global Association of Online Trainers and Examiners

Skill level:

Intermediate

Duration:

1 hour
  • Lessons (1 hour)

CPE credits:

2
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of professionals must earn to maintain their licenses and stay current with regulations and best practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's official website: www.nasbaregistry.org

Accredited

certificate

What you learn

  • Business leaders and managers planning AI adoption
  • IT managers overseeing technology modernization
  • Product and project managers working on AI initiatives
  • Professionals seeking to understand AI infrastructure

Topics & tools

Artificial IntelligenceManagementCorporate StrategyAITheory

Your instructor

Course OVERVIEW

Description

CPE Credits: 2 Field of Study: Business Mgmt & Org
Delivery Method: QAS Self Study

Successful AI adoption requires the right technology foundation. This course introduces the core components of a modern AI tech stack and explains how they work together to support business applications.

You’ll explore how to integrate AI with legacy systems, compare cloud, on-premises, and hybrid infrastructure, and evaluate open-source versus proprietary AI tools. You’ll also learn how APIs and middleware connect systems and why modular architecture helps your technology stack evolve.

By the end of the course, you’ll be better equipped to assess technology options and contribute to decisions about your organization’s AI infrastructure.

Prerequisites

  • A basic understanding of AI concepts and common business software is helpful. No programming experience or prior knowledge of AI infrastructure is required.

Advanced preparation

  • None

Curriculum

10 lessons 13 exercises 1 exam
  • 1. Building Your AI Tech Stack
    30 min
    30 min
    Why the right tech stack matters Free
    Exercise Free
    Core components of an AI tech stack Free
    Exercise Free
    Updating legacy systems Free
    Exercise Free
    Cloud vs. On-premises vs. Hybrid
    Exercise
    Open source vs. Proprietary AI tools
    Exercise
    Integrating AI with business systems
    Exercise
    Future-proofing your tech stack
    Exercise
  • 2. Partnerships
    11 min
    11 min
    Why partners matter
    Exercise
    Understand the types of AI partners
    Exercise
    Choosing the right partners for your strategy
    Exercise
  • 3. Course exam
    40 min
    40 min
    Course exam

Free lessons

Why the right tech stack matters

1.1 Why the right tech stack matters

3 min

Core components of an AI tech stack

1.3 Core components of an AI tech stack

4 min

Updating legacy systems

1.5 Updating legacy systems

4 min

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365 Data Science.

ACCREDITED certificates

Craft a resume and LinkedIn profile you’re proud of—featuring certificates recognized by leading global institutions.

Earn CPE-accredited credentials that showcase your dedication, growth, and essential skills—the qualities employers value most.

  • Institute of Analytics
  • E-Learning Quality Network
  • European Agency for Higher Education and Accreditation
  • Global Association of Online Trainers and Examiners

Certificates are included with the Self-study learning plan.

A LinkedIn profile mockup on a mobile screen showing Parker Maxwell, a Certified Data Analyst, with credentials from 365 Data Science listed under Licenses & Certification. A 365 Data Science Certificate of Achievement awarded to Parker Maxwell for completing the Data Analyst career track, featuring accreditation badges and a gold “Verified Certificate” seal.

How it WORKS

  • Lessons
  • Exercises
  • Projects
  • Practice exams
  • AI mock interviews

Lessons

Learn through short, simple lessons—no prior experience in AI or data science needed.

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Exercises

Reinforce your learning with mini recaps, hands-on coding, flashcards, fill-in-the-blank activities, and other engaging exercises.

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Projects

Tackle real-world AI and data science projects—just like those faced by industry professionals every day.

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Practice exams

Track your progress and solidify your knowledge with regular practice exams.

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AI mock interviews

Prep for interviews with real-world tasks, popular questions, and real-time feedback.

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Student REVIEWS

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