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Enterprise Program Brief

Track: Azure AI Fundamentals
MicrosoftBeginner

Azure AI Fundamentals

Certification-focused foundational program introducing common AI concepts and Azure AI services for teams beginning their AI journey.

Duration

1 day

Level

Beginner

Format

Virtual, On-site, or Hybrid

Language

English

Ideal for

Business User, Technical BeginnerAI FundamentalsTailored Team DeliveryImplementation-Focused

How VNode delivers this

Who this is for, and how we run it

VNode ITeS delivers Azure AI Fundamentals as an MCT-led Microsoft program for Business User, Technical Beginner. Typical duration is 1 day (Virtual, On-site, or Hybrid). Labs follow production-shaped scenarios rather than slide-only walkthroughs. Private cohorts can shift emphasis by role mix, workspace or repo constraints, and rollout timing.

Audience Profile

Built for these roles

Built for business and technical learners who need a structured introduction to AI concepts, responsible AI, and Azure AI capabilities.

Overview

Executive overview

Certification-focused enterprise program aligned to Azure AI Fundamentals (AI-900).

Readiness

Prerequisites

  • Hands-on experience in the relevant Microsoft workload area.
  • Familiarity with core product concepts and enterprise delivery expectations.

Program Outcomes

Capabilities your teams will gain

Strengthen readiness for AI-900 certification objectives

Build deeper delivery capability in ai fundamentals scenarios

Prepare teams for more confident project execution in the target Microsoft workload

Support structured certification-led upskilling across the organization

Curriculum

Curriculum roadmap

1

AI workloads, use cases, and responsible AI principles

2

Machine learning concepts and Azure Machine Learning

3

Computer vision and natural language processing workloads

4

Generative AI capabilities and Azure OpenAI Service

5

Azure AI Services overview and practical applications

1

Module 1

AI Workloads and Responsible AI

+

Understand common AI workload types, identify use cases for prediction, anomaly detection, vision, and language. Apply Microsoft responsible AI principles including fairness, reliability, and transparency.

  • Understand common AI workload types, identify use cases for prediction, anomaly detection, vision, and language
  • Apply Microsoft responsible AI principles including fairness, reliability, and transparency
2

Module 2

Machine Learning Fundamentals

+

Describe supervised and unsupervised learning concepts, regression, classification, and clustering scenarios, and how Azure Machine Learning supports the ML model lifecycle.

  • Describe supervised
  • unsupervised learning concepts
  • classification
  • and clustering scenarios
  • and how Azure Machine Learning supports the ML model lifecycle
3

Module 3

Computer Vision and NLP Workloads

+

Understand computer vision scenarios (image classification, object detection, OCR) and NLP workloads (text analytics, language detection, question answering, translation) on Azure AI Services.

  • Understand computer vision scenarios (image classification
  • object detection
  • NLP workloads (text analytics
  • language detection
  • question answering
4

Module 4

Generative AI and Azure OpenAI

+

Describe generative AI workloads, large language model (LLM) concepts, copilot capabilities, and Azure OpenAI Service features including chat completions, embeddings, and DALL-E.

  • Describe generative AI workloads
  • large language model (LLM) concepts
  • copilot capabilities
  • and Azure OpenAI Service features including chat completions
5

Module 5

Azure AI Services in Practice

+

Explore Azure AI Services portfolio including Speech, Language, Vision, and Document Intelligence, understand provisioning models, and identify appropriate services for common scenarios.

  • Explore Azure AI Services portfolio including Speech
  • and Document Intelligence
  • understand provisioning models
  • and identify appropriate services for common scenarios

Delivery Models

Delivery models

Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend

Engagement Fit

Engagement fit

Implementation-focused labsPrivate cohort deliveryBeginner practitioner depthBusiness outcome alignment

Enterprise Customization

Enterprise customization

Tailor this program to your organization's priorities: Creates a common baseline for enterprise AI learning before teams move into implementation-focused programs.

  • Align labs to your production environment and platform priorities
  • Add focused exam-readiness reviews and instructor-led practice sessions
  • Extend into project-specific architecture or delivery coaching

Credentials

Certification & official source

  • Azure AI Fundamentals

Aligned to the official source referenced for this program.

View Official Source

Resources

Program resources

Yes. Most enterprise clients prefer private delivery scoped to role mix, timezone, and rollout timeline. We align lab environments and scenarios to your tenant context where applicable.

Delivery Capability

Enterprise-grade instruction

View delivery capability profile

MCT-led delivery

Programs led by Microsoft Certified Trainer practitioners

Enterprise program oversight

Founder-led specialist delivery with structured rollout planning

Global delivery

APAC · EMEA · Americas · Virtual & Onsite

Implementation-focused

Hands-on labs aligned to production scenarios

Engagement Confidence

A direct, founder-led review before scope, delivery model, and commercial terms are proposed.

Response window

< 1 business day

Client coverage

India + global teams

Engagement format

Virtual, on-site, hybrid