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IA Machine and Deep Learning Azure Services Fundamentals  Path Exam AI-900

il corso esplora gli AI Azure Cloud Services specificatamente dedicati per soluzioni ML , DP ed Analytics correlati. la Reference Architecture è attentamente delineata al fine della acquisizione delle competenze e della Knowledge per le "Features" e  "Capabilities" che costituisco i "building block" Component per la varie implementazioni adottabili. 
il corso esplora le principali metodologie e tecnologie in materia di Tools, Platform dei Servizi Cloud Microsoft Azure dedicati al capitolo "Intelligenza Artificiale"  

DURATA

min 10 gg piano formativo personalizzabile

ATTESTATI

Attestato di partecipazione First Consulting 

CERTIFICAZIONI

Propedutico
Exam
AI-900

KEY POINT

Azure Service ML , DL
Intelligenza Artificiale
Azure ML Platform

Programma

Describe Artificial Intelligence workloads and considerations

Identify features of common AI workloads

  • identify prediction/forecasting workloads

  • identify features of anomaly detection workloads

  • identify computer vision workloads

  • identify natural language processing or knowledge mining workloads

  • identify conversational AI workloads

Identify guiding principles for responsible AI

  • describe considerations for fairness in an AI solution

  • describe considerations for reliability and safety in an AI solution

  • describe considerations for privacy and security in an AI solution

  • describe considerations for inclusiveness in an AI solution  describe considerations for transparency in an AI solution

  • describe considerations for accountability in an AI solution

 

Describe fundamental principles of machine learning on Azure

Identify common machine learning types

  • identify regression machine learning scenarios

  • identify classification machine learning scenarios

  • identify clustering machine learning scenarios

Describe core machine learning concepts

  • identify features and labels in a dataset for machine learning

  • describe how training and validation datasets are used in machine learning

  • describe how machine learning algorithms are used for model training

  • select and interpret model evaluation metrics for classification and regression

Identify core tasks in creating a machine learning solution

  • describe common features of data ingestion and preparation

  • describe feature engineering and selection

  • describe common features of model training and evaluation

  • describe common features of model deployment and management

Describe capabilities of no-code machine learning with Azure Machine Learning studio

  • automated ML UI

  • azure Machine Learning designer

Describe features of computer vision workloads on Azure 

Identify common types of computer vision solution:

  • identify features of image classification solutions

  • identify features of object detection solutions

  • identify features of optical character recognition solutions

  • identify features of facial detection, facial recognition, and facial analysis solutions Identify

  • Azure tools and services for computer vision tasks

  • identify capabilities of the Computer Vision service

  • identify capabilities of the Custom Vision service

  • identify capabilities of the Face service

  • identify capabilities of the Form Recognizer service

Describe features of Natural Language Processing (NLP) workloads on Azure

Identify features of common NLP Workload Scenarios

  • identify features and uses for key phrase extraction

  • identify features and uses for entity recognition

  • identify features and uses for sentiment analysis

  • identify features and uses for language modelling

  • identify features and uses for speech recognition and synthesis

  • identify features and uses for translation

Identify Azure tools and services for NLP workloads

  • identify capabilities of the Text Analytics service

  • identify capabilities of the Language Understanding service (LUIS)

  • identify capabilities of the Speech service

  • identify capabilities of the Translator Text service

 

 

Describe features of conversational AI workloads on Azure

Identify common use cases for conversational AI

  • identify features and uses for webchat bots

  • identify common characteristics of conversational AI solutions

Identify Azure services for conversational AI

  • identify capabilities of the QnA Maker service

  • identify capabilities of the Azure Bot service

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