AI-900 Azure AI Fundamentals Ausbildung





AI-900 Azure AI Fundamentals Ausbildung
AI-900 Azure AI Fundamentals E-Learning Zertifizierte Lehrer Prüfungsquizze Online Mentor MeasureUp Test Exam Live Labs Tipps Tricks Zertifikat.
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AI-900 Azure AI Fundamentals Ausbildung - OEM Certkit
Das Ausbildung AI-900 Azure AI Fundamentals über ein spezielles Zertifizierungspaket. 1 Jahr Zugang zu revolutionärem E-Learning, um die Prüfung Easy zu bestehen. Lassen Sie sich durch Lernen über 1 Learning Portal (LMS) mit zertifizierten Lehrern vorstellen. Exklusive 24/7-Online-Mentor- und anspruchsvolle Kurstests und Anzeigen aller Tipps und Tricks hinter den Kulissen.
Die offizielle Testprüfung ist immer garantiert und eine offizielle Teilnahmebescheinigung nach dem Training. Optionale Livelabs (zusätzliche Kosten).
Kursinhalt
AI-900: Azure AI Fundamentals: : Artificial Intelligence & Machine Learning
Course: 1 Hour, 44 Minutes
- Course Overview
- Artificial Intelligence
- Machine Learning
- Datasets and Data Manipulation
- Labeled vs. Unlabeled Data
- Features in Data
- Machine Learning Using Regression
- Machine Learning Using Classification
- Machine Learning Using Clustering
- Supervised Machine Learning
- Unsupervised Machine Learning
- Reliability and Safety in AI Algorithms and Use
- Transparency in AI Algorithms and Use
- Privacy and Security in Responsible AI
- Inclusiveness in AI Algorithms and Use
- Fairness in AI Algorithms and Use
- Accountability in AI Algorithms and Use
- Course Summary
AI-900: Azure AI Fundamentals: Machine Learning with Azure Services
Course: 1 Hour, 52 Minutes
- Course Overview
- Machine Learning Services Provided by Azure
- Azure Machine Learning Studio
- Signing up for an Azure ML Studio Account
- Inspecting the Azure Machine Learning Features
- Features of the Computer Vision Service
- Features of the Custom Vision Service
- Features of the Face Service
- Features of the Form Recognizer Service
- Identifying Azure ML Workloads
- Compute Resources
- Creating and Managing Datasets in Azure ML Studio
- Managing Pipelines in Azure ML Studio
- Algorithms Used for Model Training
- Azure ML Services Experiments
- Interpreting Evaluation Metrics for Classification
- Interpreting Model Evaluation Metrics for Regression
- Course Summary
AI-900: Azure AI Fundamentals: Using Azure Machine Learning Studio
Course: 1 Hour, 31 Minutes
- Course Overview
- Creating an Azure ML Workspace
- Creating a Compute Resource Using Azure ML Studio
- Creating and Using a Dataset in Azure ML Studio
- Ingesting Data from Azure Storage
- Ingesting Data from Azure Blob Storage
- Labeling Data in Azure ML Studio
- Running and Testing Scripts Using Notebook
- Creating an Automated ML Model
- Running an Automated Experiment
- Determining the Best Model after an Experiment
- Deploying a Model as a Predictive Service
- Testing the Predictive Service
- Managing Compute Resources and Datastores
- Managing Datasets and Experiments in Azure ML Studio
- Managing Pipelines and Models in Azure ML Studio
- Managing Endpoints in Azure ML Studio
- Course Summary
AI-900: Azure AI Fundamentals: Authoring with the Azure ML Studio Designer
Course: 1 Hour, 11 Minutes
- Course Overview
- Creating and Using a Dataset in Azure ML Designer
- Selecting Dataset Features in Azure ML Designer
- Adding Data Transformations in Azure ML Designer
- Normalizing and Cleaning Data in Azure ML Designer
- Viewing Normalized & Transformed Data in ML Designer
- Splitting a Dataset for Testing and Evaluation
- Using a Regression Model in Azure ML Designer
- Using a Classification Model in Azure ML Designer
- Using a Clustering Model in Azure ML Designer
- Course Summary
AI-900: Azure AI Fundamentals: Evaluating Models with the ML Designer
Course: 2 Hours, 3 Minutes
- Course Overview
- Adding and Using Scoring on Models
- Model Evaluation Types
- Using Evaluators on the Model
- Running a Pipeline
- Analyzing the Evaluation Results Output and Logs
- Exploring the Evaluation Results Details
- Visualizing the Data in the Scoring Model
- Investigating Results from a Regression Model
- Interpreting Results from a Classification Model
- Investigating Results from a Clustering Model
- Creating an Inference Pipeline
- Adding a Web Service Output
- Deploying a Predictive Service
- Testing a Predictive Service
- Course Summary
AI-900: Azure AI Fundamentals: Natural Language Processing
Course: 1 Hour, 6 Minutes
- Course Overview
- Natural Language Processing
- Uses of Natural Language Processing
- Azure NLP Services
- Intents and Entities
- Training a Language Model
- Using the Text Analytics Service
- Azure Translator Service
- Using the Translator Service to Translate Text
- Using the Translator Service to Translate Speech
- Course Summary
AI-900: Azure AI Fundamentals: Computer Vision
Course: 1 Hour, 23 Minutes
- Course Overview
- Computer Vision
- Azure Computer Vision Services
- Computer Vision Models
- Classify and Detect Objects
- Analyzing Images Using Computer Vision Service
- Describing and Tagging Images
- Training a Classifier Model
- Evaluating a Classifier Model
- Testing and Using a Model for Prediction
- Training an Object Detection Model
- Evaluating an Object Detection Model
- Using the Model as a Service
- Semantic Segmentation
- Course Summary
AI-900: Azure AI Fundamentals: Face & Optical Character Recognition
Course: 1 Hour, 55 Minutes
- Course Overview
- Face Detection
- Using Computer Vision for Face and Age Detection
- Using Video Indexer to Identify Faces in Videos
- Using the Face Service to Detect and Analyze Faces
- Optical Character Recognition API
- Using Computer Vision to Read Text
- Using Computer Vision to Read Text from Photographs
- Reading Text from Digitized Documents
- Form Recognizer Service
- Read API
- Using the Pre-built Receipt Model
- Using a Custom Form Recognizer Model1
- Identifying Specific Fields and Types on a Receipt
- Processing Tables on Forms
- Course Summary
Unterrichtsdauer | 12:42 Stunde |
---|---|
Sprache | Englisch |
Online-Zugang | 365 Tage |
Teilnahmeurkunde | Ja |
Preisgekröntes Online-Training | Ja |
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