AI-900 EXAM QUESTIONS 2024 WITH PERSONAL NOTES PART-1

AI-900 EXAM QUESTIONS 2024 WITH PERSONAL NOTES PART-1

Hello everyone, and welcome back to our channel! In today’s article, we’ll dive deep into the AI-900 exam questions along with my personal notes. We'll discuss everything from the Microsoft principles for responsible AI to different services under Azure AI, and I'll share my experience and insights. Whether you’ve just cleared the AI-900 exam like I did with a 98.5% score or you’re preparing for it, this article will serve as a comprehensive guide.

Preparing for AI-900 Exam: My Personal Journey

I recently cleared the AI-900 exam, which is a Microsoft Azure Fundamental exam. Though it’s considered to be simple, it can be tricky. During the exam, you might feel all options in the questions are correct, but understanding the key principles and services will guide you to the right answers.

If you are new to AI and looking for a foundational certification, AI-900 is a great start, especially in the early phase of AI revolution. Here’s a rundown of the critical points covered in my notes which helped me greatly in the exam.

Microsoft’s Six Guiding Principles for Responsible AI

The exam focuses heavily on these principles, making up around 20-25% of the questions. These principles are straightforward but very crucial. Here are the six guiding principles:

1. Transparency
2. Accountability
3. Privacy and Security
4. Fairness
5. Inclusiveness
6. Reliability and Safety

Understanding the Principles

• Transparency: Ensure the AI model's operation is transparent. Explain what the model does and its limitations.
• Accountability: AI should adhere to legal, ethical standards and organization policies. Human intervention must be possible.
• Privacy and Security: Users should have control over how their data is collected and used.
• Fairness: The AI should not exhibit bias and must treat all users equally.
• Inclusiveness: Design AI solutions that empower everyone, including those with disabilities.
• Reliability and Safety: AI should function as intended and handle unexpected scenarios without harmful manipulation.

Helping You Remember

A good way to remember these is by using the first letter of each principle: TAP FAIR.

Five Key Elements of Microsoft AI

Microsoft AI is divided into five major categories:

1. Machine Learning (ML)
2. Computer Vision
3. Natural Language Processing (NLP)
4. Conversational AI
5. Anomaly Detection

Each has its significance and examples, which I'll cover:

• Machine Learning (ML): Learning from datasets to make decisions without being explicitly programmed.
• Computer Vision: Analyzing visual data through images and videos.
• Natural Language Processing (NLP): Understanding and generating human language.
• Conversational AI: Chatbots and virtual agents that interact using a knowledge base.
• Anomaly Detection: Identifying unusual or potentially fraudulent activities.

Detailed Breakdown of AI Services

Anomaly Detection

Used for identifying potentially fraudulent transactions, learning patterns to indicate network intrusions, and more.

Conversational AI

Automated chat systems answering customer queries using a pre-defined knowledge base, mainly supported by knowledge mining.

Computer Vision

Live cameras, images, and video analysis fall under this. For instance, self-driving cars utilize computer vision to monitor their surroundings.

Natural Language Processing (NLP)

NLP can be broken into various services and features like:

• Text Analytics: Sentiment analysis, key phrase extraction, language detection.
• Q&A Maker: Creating a knowledge base from documents with FAQ styled Q&A.
• Language Understanding (LUIS): Understanding the intent behind user inputs, although it's been largely replaced by newer services.

Speech Services

• Text-to-Speech (TTS) and Speech-to-Text (STT): Converting text to speech and vice versa.
• Speech Translation: Translating one spoken language to text in another language.

Practice Questions and Common Pitfalls

While practicing, pay close attention to the wording of questions. Here’s a sample question you might come across:

Question: “You're designing an AI system that empowers everyone, including people with hearing and visual impairments. Which Microsoft guiding principle does this exemplify?”

Answer: Inclusiveness

Other tricky areas often involve distinguishing between similar-looking options, so make sure you understand the specific context of each principle and service.

Keywords

Keywords:

• Transparency
• Accountability
• Privacy and Security
• Fairness
• Inclusiveness
• Reliability and Safety
• Machine Learning
• Computer Vision
• Natural Language Processing
• Conversational AI
• Anomaly Detection
• Text Analytics
• Sentiment Analysis
• Named Entity Recognition
• Q&A Maker
• Speech-to-Text
• Text-to-Speech

FAQ

FAQ:

1. What are Microsoft’s six guiding principles for responsible AI?

   • Transparency, Accountability, Privacy and Security, Fairness, Inclusiveness, and Reliability and Safety.

2. What is anomaly detection in AI?

   • It identifies unusual patterns or behaviors that deviate from the norm, useful in detecting fraud or network intrusions.

3. What services fall under natural language processing (NLP)?

   • Services include Text Analytics, Q&A Maker, and previously LUIS (Language Understanding Intelligent Service).

4. What is the difference between text-to-speech and speech-to-text services?

   • Text-to-Speech (TTS) converts written text into spoken words, whereas Speech-to-Text (STT) converts spoken words into written text.

5. How does the AI-900 exam test your understanding of principles like transparency and accountability?

   • The exam presents scenarios requiring you to apply these principles, such as ensuring proper documentation and transparency about an AI model’s operations.

By spending time with these principles and understanding the services well, you’ll be well-prepared to tackle the AI-900 exam efficiently. Make sure to review, practice, and explore all these elements comprehensively.