Microsoft has made a wide range of certification opportunities available to all users. They are intended to prepare professionals for the rapidly changing job roles in technology. To begin, the Microsoft Azure AI Fundamentals (AI-900) exam allows you to demonstrate your understanding of common ML and AI workloads and how to implement them on Azure. Furthermore, the Microsoft Azure AI Fundamentals (AI-900) exam is designed for candidates with fundamental knowledge of machine learning (ML), artificial intelligence (AI), and related Microsoft Azure services.
Let us know how to pass the Microsoft Azure AI Fundamentals (AI-900) exam!
About Microsoft Azure AI Fundamentals (AI-900) exam
This exam is designed for both technical and non-technical candidates. Experience in data science and software engineering is not required; however, some general programming knowledge or experience would be advantageous. The Azure AI Fundamentals can also be used to prepare for other Azure role-based certifications, such as Azure Data Scientist Associate or Azure AI Engineer Associate, but it is not required for any of them.
Candidates for this exam should have a solid understanding of machine learning (ML) and artificial intelligence (AI) concepts, as well as the Microsoft Azure services that support them. This exam allows you to demonstrate your understanding of common ML and AI workloads and how to implement them on Azure.
Learning Objectives
Before preparing for an exam, Microsoft provides exam objectives to assist candidates in understanding and learning about the concepts. Furthermore, these exam concepts are divided into sections and subsections to help you learn them thoroughly. Microsoft’s basic concepts for AI-900 are as follows:
- Workloads and considerations for AI
- The fundamentals of machine learning on Azure
- Features of Azure computer vision workloads and Azure Natural Language Processing (NLP) workloads
- Conversational AI workloads on Azure characteristics
Now that you are aware of the exam in detail, let us now move on to the step-by-step guide for How to pass the Microsoft Azure AI Fundamentals (AI-900) exam!
How to pass the Microsoft Azure AI Fundamentals (AI-900) exam?
Passing the exam demonstrates professional competence in core subject areas covered by the corresponding Microsoft exam, as well as the ability to begin a career developing applications for Microsoft Windows operating systems. This is a detailed guide on How to Pass the Microsoft Azure AI Fundamentals (AI-900) Exam.
Step 1 – Know about the exam syllabus
Here is the detailed exam content outline –
Topic 1: Describe Artificial Intelligence workloads and considerations (15-20%)
1.1 Identify features of common AI workloads
- identifying the features of data monitoring and anomaly detection workloads Anomaly Detector)
- Identify features of content moderation and personalization workloads
- identify computer vision workloads (Microsoft Documentation: Applying content tags to images, Detect common objects in images, Detect popular brands in images)
- identifying natural language processing workloads (Microsoft Documentation: Choosing a natural language processing technology in Azure)
- identify knowledge mining workloads (Microsoft Documentation: Explore knowledge mining)
- Identify document intelligence workloads
- Identify features of generative AI workloads
1.2 Identify guiding principles for responsible AI
- describing the considerations for fairness in an AI solution (Microsoft Documentation: Model performance and fairness (preview))
- explaining the considerations for reliability and safety in an AI solution (Microsoft Documentation: Responsible and trusted AI)
- describing the considerations for privacy and security in an AI solution (Microsoft Documentation: Responsible AI)
- explaining the considerations for inclusiveness in an AI solution (Microsoft Documentation: Responsible and trusted AI)
- describing considerations for transparency in an AI solution (Microsoft Documentation: Identify guiding principles for responsible AI)
- describing considerations for accountability in an AI solution (Microsoft Documentation: Responsible and trusted AI, Identify guiding principles for responsible AI)
Topic 2: Describe fundamental principles of machine learning on Azure (20-25%)
2.1 Identify common machine learning techniques
- identifying regression machine learning scenarios (Microsoft Documentation: Linear Regression)
- identifying classification machine learning scenarios (Microsoft Documentation: Classification modules)
- identify clustering machine learning scenarios (Microsoft Documentation: Clustering modules)
- Identify features of deep learning techniques
2.2 Describe core machine learning concepts
- identifying features and labels in a dataset for machine learning (Microsoft Documentation: Create and explore Azure Machine Learning dataset with labels)
- explaining how training and validation datasets are used in machine learning (Microsoft Documentation: Configure training, validation, cross-validation and test data in automated machine learning)
2.3 Describe Azure Machine Learning capabilities
- Describe capabilities of Automated machine learning (Microsoft Documentation: Automated machine learning (AutoML))
- Describe data and compute services for data science and machine learning
- Describe model management and deployment capabilities in Azure Machine Learning
Topic 3: Describe features of computer vision workloads on Azure (15-20%)
3.1 Identify common types of computer vision solution:
- identifying features of image classification solutions (Microsoft Documentation: Train image classification models with MNIST data and scikit-learn)
- identify features of object detection solutions (Microsoft Documentation: Detect common objects in images)
- identifying features of optical character recognition solutions (Microsoft Documentation: Optical Character Recognition (OCR))
- identify features of facial detection and facial analysis solutions
3.2 Identify Azure tools and services for computer vision tasks
- Describe capabilities of the Azure AI Vision service
- Describe capabilities of the Azure AI Face detection service
- Describe capabilities of the Azure AI Video Indexer service
Topic 4: Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)
4.1 Identify features of common NLP Workload Scenarios
- identifying features and uses for key phrase extraction (Microsoft Documentation: How to extract key phrases using Text Analytics)
- identify the features and uses for entity recognition (Microsoft Documentation: Entity Recognition cognitive skill)
- identifying features and uses for sentiment analysis (Microsoft Documentation: What is sentiment analysis and opinion mining)
- identifying features and uses for language modeling (Microsoft Documentation: language detection in Azure Cognitive Service for Language)
- identify the features and uses for speech recognition and synthesis (Microsoft Documentation: Get started with speech-to-text, Speech service)
- identifying features and uses for translation (Microsoft Documentation: Translator service)
4.2 Identify Azure tools and services for NLP workloads
- identifying capabilities of the Azure AI Language Service (Microsoft Documentation: Azure Cognitive Service for Language)
- identify the capabilities of the Azure AI Speech service (Microsoft Documentation: Speech service)
- identify the capabilities of the Azure AI Translator service
5. Describe features of generative AI workloads on Azure (15–20%)
5.1 Identify features of generative AI solutions
- Identify features of generative AI models
- Identify common scenarios for generative AI
- Identify responsible AI considerations for generative AI
5.2 Identify capabilities of Azure OpenAI Service
- Describe natural language generation capabilities of Azure OpenAI Service
- Describe code generation capabilities of Azure OpenAI Service
- Describe image generation capabilities of Azure OpenAI Service
Step 2 – Know about the exam Format
The Microsoft Azure AI Fundamentals (AI-900) exam consists of 40-60 multiple-choice questions. The Microsoft Azure AI-900 exam may contain scenario-based single answer questions, multiple-choice questions, arrange in the correct sequence type questions, drag & drop questions, mark review, drag and drop, and so on.
To pass the exam, however, a candidate must obtain a score of 700 or higher. The examination fee, including taxes, is USD 99 to apply for the exam. Candidates for the AI-900 exam will have the option of taking the exam in English, Japanese, Chinese (Simplified), Korean, German, French, or Spanish.
Step 3 – Know about the exam policies
Some of the important policies that you need to know are –
Exam retake policy: MD-100
If you did not pass the exam on the first try, remember that it is not the end of the road, but only a minor hiccup. Furthermore, Microsoft allows you five attempts per year on a particular exam. The retake policy for exams is as follows:
- If a candidate fails to pass the exam on the first try, he or she must wait at least 24 hours before retaking the exam.
- Furthermore, If a candidate fails the exam the second time, he or she must wait at least 14 days before retaking it a third time.
- There is also a 14-day waiting period for the fourth and fifth subsequent exam retakes.
Cancellation and Reschedule Policy
Microsoft allows you to cancel the Exam for free up to 24 hours before your scheduled appointment. However, if you do not show up for your exam without rescheduling or canceling it, Microsoft reserves the right to forfeit your entire exam fee. Furthermore, Using the Certification Dashboard, you can reschedule, cancel, or schedule the Microsoft MD-100 exam.
Step 4 – Create a Study Plan
The next step is to devise a study strategy for your preparations. Keep in mind the course topics and the time remaining for the real exam when creating the plan. Remember to start by strengthening your weaker areas. Furthermore, pay close attention to topics that have a higher weightage in the exam. Following your plan will help you stay consistent and avoid distractions. The key to excelling is to get started early, so get started with your preparations and stay motivated.
Step 5 – Refer to official Resources
Microsoft offers training courses, Microsoft MD-100 exam dumps, and study materials to equip you with the necessary tools. These Microsoft Exam MD-100 training courses will assist you in preparing for the exam by providing you with hands-on experience and training. Microsoft offers two types of training courses:
Free Learning paths –
- Firstly, Microsoft Azure AI Fundamentals: Get started with artificial intelligence
- Also, Microsoft Azure AI Fundamentals: Explore visual tools for machine learning
- In addition, Microsoft Azure AI Fundamentals: Explore computer vision
- Also, Microsoft Azure AI Fundamentals: Explore natural language processing
- Finally, Microsoft Azure AI Fundamentals: Explore conversational AI
Instructor-led courses –
Step 6 – Refer to Learning resources
These are some of the resources in addition to the official resources –
- Microsoft Documentation – When studying for exams, Microsoft Documentation is a valuable resource. The candidate will be able to find documentation on every topic related to the specific exam.
- Instructor-Led Training– Micorosft’s training programs are available on their website. Instructor-led training is an essential resource for preparing for exams such as Microsoft Azure AI Fundamentals (AI-900).
- Testprep Online Tutorials – Microsoft Azure AI Fundamentals (AI-900) on Azure Online Tutorial broadens your knowledge and provides a thorough understanding of exam concepts. They also go over exam specifics and policies. As a result, learning with Online Tutorials will help you prepare better.
- Practice Tests – A practice test ensures the candidate’s preparation. The practice test will assist candidates in identifying their weak points so that they can work on them. There are numerous practice tests available on the internet these days, so the candidate can select which one they prefer. We at Testprep training also provide practice tests, which are extremely beneficial to those who are preparing.
Step 7 – Take the Exam
After practising and consulting appropriate resources, you are now prepared to take the exam. Keep your cool and patience while taking the exam. The significance of time management in exam preparation cannot be overstated. As a result, we recommend that you prepare for the AI-900 Exam on a regular basis. Ideally, you should study at the same time every day. Make sure there are no distractions when studying.
Conclusion
Professional certifications prepare you for a job and give you a competitive advantage. Preparing for a certification exam is similar to planning for any major goal. This Microsoft Azure AI-900 exam will help you quickly advance up the corporate ladder. The course’s hands-on exercises are based on Learn modules, and students are encouraged to use the content on Learn as reference materials to reinforce what they learn in class and to delve deeper into topics.
