Microsoft Certified Azure AI Fundamentals Crash Course
Duration: 2h 15m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 330 MB
Genre: eLearning | Language: English
Duration: 2h 15m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 330 MB
Genre: eLearning | Language: English
Artificial intelligence is no longer an abstract concept. It’s being used here and now by companies of all sizes and industries. To meet the growing demand for AI and machine learning professionals, Microsoft has created the Exam AI-900: Microsoft Azure AI Fundamentals. Earning this entry-level certification could help jumpstart your career in one of the most exciting areas of IT.
Join expert Emilio Melo to learn everything you need to successfully prepare for the Azure AI Fundamentals exam. You’ll walk through the most important topics on the exam, such as machine learning and cognitive services technologies in vision, NLP, and conversational AI—and identify gaps in your Azure knowledge so that you know exactly what to focus on when getting ready for the exam.
What you’ll learn and how you can apply it
By the end of this course, you’ll understand:
The most appropriate workloads for artificial intelligence
The core concepts and domains being tested by the Microsoft Azure AI Fundamentals (AI-900) exam
Key concepts related to creating and consuming Azure AI solutions
The fundamental principles of AI workloads on Microsoft Azure, including computer vision, natural language processing, conversational AI, and machine learning
And you’ll be able to:
Pinpoint the most appropriate AI solutions for specific customer requirements
Identify gaps in your Azure knowledge
Describe features of conversational AI workloads on Azure
Differentiate between various data science experiments, including classification, regression, clustering, anomaly detection, and reinforcement learning
This course is for you because…
You’re a business or IT professional who wants to become more familiar with data and AI workloads, and see the AI-900 certification as a good stepping stone to prove your value.
You work with AI workloads and need to certify your knowledge of the area.
You want to become an Azure AI engineer.
Prerequisites
Familiarity with data and cloud solutions (useful but not required)