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Career Opportunities
As you remember, the Microsoft Certified: Azure AI Fundamentals validation is the fundamental certification designed for beginners with both technical and non-technical backgrounds. It is considered a good path to follow if you're interested in starting a career in the field of AI and ML. Below are some of the jobs that you can get your hand on through this certification. These jobs come with decent annual salaries as covered by Payscale.com:
- AI Engineer: $76k;
- Developer: $50k;
- Data Scientist: $67k.
Nowadays the knowledge capabilities and mental labor are more valuable than the manual labor because knowledge can create more wealth than the mental labor. If you boost professional knowledge capabilities in some area you are bound to create a lot of values and can get a good job with high income. Passing the test of Microsoft certification can help you achieve that, and our AI-900日本語 training materials are the best study materials for you to prepare for the test. Our AI-900日本語 guide materials combine the key information about the test in the past years' test papers and the latest emerging knowledge points among the industry to help the clients both solidify the foundation and advance with the times. We give priority to the user experiences and the clients' feedback, AI-900日本語 practice guide will constantly improve our service and update the version to bring more conveniences to the clients and make them be satisfied. The clients' satisfaction degrees about our AI-900日本語 training materials are our motive force source to keep forging ahead. Now you can have an understanding of our AI-900日本語 guide materials.
Microsoft AI-900 Exam Syllabus Topics:
| Topic | Details |
|---|---|
Describe Artificial Intelligence workloads and considerations (20-25%) | |
| Identify features of common AI workloads | - identify features of anomaly detection workloads - identify computer vision workloads - identify natural language processing workloads - identify knowledge mining workloads |
| Identify guiding principles for responsible AI | - describe considerations for fairness in an AI solution - describe considerations for reliability and safety in an AI solution - describe considerations for privacy and security in an AI solution - describe considerations for inclusiveness in an AI solution - describe considerations for transparency in an AI solution - describe considerations for accountability in an AI solution |
Describe fundamental principles of machine learning on Azure (25-30%) | |
| Identify common machine learning types | - identify regression machine learning scenarios - identify classification machine learning scenarios - identify clustering machine learning scenarios |
| Describe core machine learning concepts | - identify features and labels in a dataset for machine learning - describe how training and validation datasets are used in machine learning |
| Describe capabilities of visual tools in Azure Machine Learning studio | - automated machine learning - azure Machine Learning designer |
Describe features of computer vision workloads on Azure (15-20%) | |
| Identify common types of computer vision solution | - identify features of image classification solutions - identify features of object detection solutions - identify features of optical character recognition solutions - identify features of facial detection, facial recognition, and facial analysis solutions |
| Identify Azure tools and services for computer vision tasks | - identify capabilities of the Computer Vision service - identify capabilities of the Custom Vision service - identify capabilities of the Face service - identify capabilities of the Form Recognizer service |
Describe features of Natural Language Processing (NLP) workloads on Azure (25-30%) | |
| Identify features of common NLP Workload Scenarios | - identify features and uses for key phrase extraction - identify features and uses for entity recognition - identify features and uses for sentiment analysis - identify features and uses for language modeling - identify features and uses for speech recognition and synthesis - identify features and uses for translation |
| Identify Azure tools and services for NLP workloads | - identify capabilities of the Language service - identify capabilities of the Speech service - identify capabilities of the Translator service |
| Identify considerations for conversational AI solutions on Azure | - identify features and uses for bots - identify capabilities of the Azure Bot service |
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
Preparation Process
Microsoft offers a wide range of resources to help you prepare for your certification exam. The first step in the preparation process is to go through the topics in detail. This will enable you to understand the specific areas that are covered in the test. With this understanding, you can start to get the materials that will provide more knowledge on the objectives. Thus, Microsoft comes with two training options to help the candidates develop the required skills. These are free online training and instructor-led training.
- Instructor-Led Training: The Microsoft Azure AI Fundamentals course is designed to help you gain the required skills to pass the exam and obtain the certification. It introduces the learners to the fundamental concepts of AI and the services available in Microsoft Azure that are useful in creating AI solutions. This training is delivered by the certified partners and its details can be found on the Microsoft website. It is important to mention that this course is designed to be combined with other online materials that are available on the Microsoft Learning platform.
- Practice Test: As a future examinee, you also have access to the official practice test to evaluate your understanding of the exam topics before taking the actual test. The link to this training tool can be found on the Microsoft website.
- Free Online Training: The individuals can explore five free training tutorials that are available on the official exam webpage. They have a series of modules that focus on the specific domains of the test. These training tutorials are recommended for those candidates who are comfortable with the self-paced study. The topics of these manuals include the following options:
- Get Started with AI on Azure;
- Create No-Code Predictive Models with Azure ML;
- Explore NLP;
- Explore Computer Vision on Microsoft Azure;
- Explore Conversational Artificial Intelligence.
The students can find the details of these learning paths on the official website.
Career Prospects
Although the Microsoft AI-900 exam is associated with the foundational-level certification, all the successful candidates can pursue various lucrative career paths in the field of IT. Some of the job roles that these professionals can work in include a Data Scientist, a Software Developer, and an Azure AI Engineer, among others. They can also proceed to get some other role-based certificates to boost their potential in the world of Information Technology. With the Microsoft Certified: Azure AI Fundamentals certification, you can earn an average of $48,000 per annum as an entry-level specialist. Those with some work experience can get an average of $74,000 per year.
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