[NEW] AI-900: Microsoft Azure AI Fundamentals exam practice

Description

Synthetic intelligence and machine studying are all set to dictate the way forward for know-how. The main focus of Microsoft Azure on machine-learning innovation is likely one of the distinguished causes for the rising reputation of Azure AI. Subsequently, many aspiring candidates are on the lookout for credible approaches for the AI-900 exam preparation that may be a viable instrument for candidates to start out their careers in Azure AI.

Exam Format and Info

Exam Title Exam AI-900: Microsoft Azure AI Fundamentals

Exam Period 60 Minutes

Exam Sort A number of Alternative Examination

Variety of Questions 40 – 60 Questions

Exam Price $99

The AI-900 exam covers the next subjects:

• Describe AI workloads and issues (15-20%)

• Describe elementary ideas of machine studying on Azure (30-35%)

• Describe options of pc imaginative and prescient workloads on Azure (15-20%)

• Describe options of Pure Language Processing (NLP) workloads on Azure (15-20%)

• Describe options of conversational AI workloads on Azure (15-20%)

1: Describing AI workloads and issues

The subtopics on this area embody

• Identification of guiding ideas for accountable AI

• Identification of options in frequent AI workloads

2: Describing elementary ideas of machine studying on Azure

The subtopics on this area embody,

• Identification of frequent machine studying variants

• Identification of core dangers within the creation of a machine studying answer

• Description of capabilities of no-code machine studying with Azure Machine Studying

• Description of core machine studying ideas

3: Description of options in pc imaginative and prescient workloads on Azure

The subtopics on this area embody,

• Identification of frequent sorts of pc imaginative and prescient options

• Identification of Azure instruments and providers for pc imaginative and prescient duties

4: Describing options of Pure Language Processing (NLP) workloads on Azure

The subtopics on this area are as follows

• Figuring out Azure instruments and providers for NLP workloads

• Identification of options in frequent NLP workload situations

5: Description of options of conversational AI workloads on Azure

The subtopics on this area embody,

• Figuring out Azure providers for conversational AI

• Identification of frequent use instances for conversational AI