Introduction:
Embarking on the journey to master Artificial Intelligence (AI) can be both exhilarating and challenging, when I got my masters in AI and Machine learning I thought I had the right skills to get it done, but I was wrong, I felt I needed to get on the next step which is getting certifications to back it up. I felt like there was no better way to start than as I delved into the AI-900 certification. This blog aims to document my experiences, insights, and the hurdles I’ve faced while navigating through the AI-900 tutorial and exam. From understanding the fundamentals of machine learning algorithms to grasping the intricacies of natural language processing, this certification has been a whirlwind of learning and growth.
1. Understanding the AI-900 Exam:
The AI-900 exam, also known as Microsoft Azure AI Fundamentals, is designed for individuals who want to demonstrate their foundational knowledge of artificial intelligence (AI) concepts and related Microsoft Azure services. It is an ideal starting point for those interested in AI, regardless of technical background.
2. Key Topics Covered:
To excel in the AI-900 exam, it is crucial to have a solid understanding of the following key topics:
Azure AI Services
- Azure Machine Learning: This part delves into Azure’s machine learning service, which allows you to build, train, and deploy machine learning models. You’ll learn about the Azure ML Studio, automated ML, and various ML algorithms.
- Computer Vision: This section focuses on Azure’s computer vision capabilities, including image analysis, facial recognition, and object detection.
- Natural Language Processing (NLP): Here, you’ll learn about Azure’s Text Analytics service, which can perform sentiment analysis, key phrase extraction, and language detection. You’ll also explore Azure’s Translator service.
- Speech: This part covers Azure’s speech services, including speech-to-text, text-to-speech, and speech translation.
- Conversational AI: This section introduces you to Azure’s Bot Services, which allow you to build, test, and deploy intelligent bots that can interact naturally with users.
Data and AI Workloads
- Data Workloads: This part covers the basics of working with data in Azure, including Azure Blob Storage and Azure Data Lake Storage.
- AI Workloads: This section focuses on how to implement AI solutions using Azure services, including considerations for responsible AI.
Additional Topics
- Security and Compliance: This part touches on how to secure your AI solutions and ensure they comply with relevant regulations.
- Monitoring and Management: This section covers how to monitor the health and performance of your AI services.
- Ethics in AI: this is a major section to understand as you take the exam as it Is covered heavily in the ai-900 exam.
Each of these topics is accompanied by practical exercises and examples, usually within the Azure portal, to help you gain hands-on experience.
4. Answering Common Exam Questions:
To help you tackle some common question formats in the AI-900 exam, here are a few tips:
1. Multiple-choice questions: Read the question carefully, eliminate obviously incorrect options, and choose the best-fit answer based on your knowledge.
2. Scenario-based questions: Analyze the given scenario thoroughly, identify the problem or requirement, and apply your understanding of AI concepts to determine the most appropriate solution.
3. Fill-in-the-blank questions: Pay attention to the expected answer format and ensure correct spelling. Utilize contextual clues from the question to fill in the missing word(s).
4. True/False questions: Be cautious, as a single incorrect statement makes the entire answer false. Carefully evaluate each statement before answering.
5. below is the breakdown of the exam as of August 4, 2023:
- Describe Artificial Intelligence workloads and considerations (20–25%)
- Describe fundamental principles of machine learning on Azure (25–30%)
- Describe features of computer vision workloads on Azure (15–20%)
- Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
we will go over some of these in my next few blogs as we journey further into each section.
Conclusion:
Preparing for the AI-900 exam requires a solid grasp of AI concepts and familiarity with Microsoft Azure AI services. By following the strategies mentioned above and in my blog, you can confidently approach the exam. Remember, continuous learning and hands-on experience with Azure AI services will enhance your understanding and improve your chances of success.