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    AI-900 Course Azure AI Fundamentals with Virtual Simulations

    Posted By: lucky_aut
    AI-900 Course Azure AI Fundamentals with Virtual Simulations

    AI-900 Course Azure AI Fundamentals with Virtual Simulations
    Published 9/2023
    Duration: 4h 56m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 2.84 GB
    Genre: eLearning | Language: English

    Get prepared for the AI-900 exam with instructor led labs and hands on simulations available 24/7

    What you'll learn
    Learn the concepts and perform hands on activities needed to pass the AI-900 exam
    Gain a tremendous amount of knowledge involving advanced Azure AI Services
    Get loads of hands on experience with Azure AI Services
    Utilize hands on simulations that can be access anytime, anywhere!
    Requirements
    Willingness to put in the time and practice the steps shown in the course
    Description
    We really hope you'll agree, this training is way more than the average course on Udemy!
    Have access to the following:
    Training from an instructor of over 20 years who has trained thousands of people and also a Microsoft Certified Trainer
    Lecture that explains the concepts in an easy to learn method for someone that is just starting out with this material
    Instructor led hands on and simulations to practice that can be followed even if you have little to no experience
    TOPICS COVERED INCLUDING HANDS ON LECTURE AND PRACTICE TUTORIALS:
    Introduction
    Welcome to the course
    IMPORTANT Using Assignments in the course
    Creating a free Azure Account
    Order of concepts covered in the course
    Introduction to artificial intelligence terminology
    Identify features of common AI workloads
    Understanding features of anomaly detection workloads
    Example of univariate anomaly detection
    Example of multivariate anomaly detection
    What is computer vision workloads?
    Conceptual usage of natural language processing workloads
    Visualizing knowledge mining principals
    Identify guiding principles for responsible AI
    Introduction to responsible AI
    Fairness and Inclusiveness in an AI solution
    Reliability and safety in an AI solution
    Privacy and security in an AI solution
    Transparency in an AI solution
    Accountability in an AI solution
    Identify common machine learning types
    Create an Azure Machine Learning workspace for machine learning scenarios
    What is regression machine learning?
    Building a pipeline with regression machine learning for cleaning a dataset
    Implement a regression machine learning scenario
    Evaluating the results of regression machine learning scenarios
    What is classification machine learning?
    Implement a classification machine learning scenario in Azure
    Understanding labels on a confusion matrix
    Clustering machine learning example
    Describe core machine learning concepts
    Understanding features and labels in a dataset for machine learning
    How training and validation datasets are used in machine learning
    Describe capabilities of visual tools in Azure Machine Learning Studio
    Using Automated machine learning
    Understanding Azure Machine Learning Designer
    Cleaning up our existing Azure resources
    Identify common types of computer vision solutions
    What are the Azure computer vision solutions?
    Creating an Azure computer vision resource
    Image classification and object detection solutions in vision studio
    Optical character recognition solutions in vision studio
    Facial detection and facial analysis solutions in vision studio
    Spatial analysis solutions in vision studio
    Identify Azure tools and services for computer vision tasks
    Using the POSTMAN tool for interacting with Azure AI Services
    Implementing the capabilities of the Computer Vision service
    Implementing the capabilities of the Custom Vision service
    Implementing the capabilities of the Face service
    Implementing the capabilities of the Form Recognizer service
    Identify features of common NLP Workload Scenarios
    What are the Azure AI Language features?
    Creating a language service resource in Azure
    Trying out key phrase extraction
    Trying out key entity recognition
    Trying out key sentiment analysis
    Trying out key language modeling
    Trying out key speech recognition and synthesis
    Trying out key translation
    Identify Azure tools and services for NLP workloads
    Exploring the capabilities of the Language service
    Exploring the capabilities of the Speech service
    Exploring the capabilities of the Translator service
    Configuring Azure AI language to support questions and answers support
    Identify considerations for conversational AI solutions on Azure
    Understanding the features and uses for bots
    Capabilities of Power Virtual Agents and the Azure Bot service
    Remove existing resource
    Who this course is for:
    IT people interested in learning and passing the Microsoft AI-900 exam!

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