The AI102 exam is for the Microsoft Certified: Azure AI Engineer Associate certification. This certifies your ability to build, manage, and deploy AI solutions on Microsoft Azure using services like Cognitive Services, Cognitive Search, and Bot Framework.
Passing this exam requires expertise in:
- Planning and managing Azure AI solutions
- Implementing decision support solutions
- Implementing computer vision solutions
- Implementing natural language processing solutions
- Implementing knowledge mining and document intelligence solutions
- Implementing generative AI solutions
You also need proficiency in C# or Python and experience with REST APIs.
Here are some tips to pass the AI102 exam:
Study the Exam Skills Outline
Microsoft publishes a detailed skills outline for the exam. Carefully review this to understand the topics tested. The outline was updated on February 7, 2024, so review changes since your last attempt.
Take Practice Tests
Microsoft offers an official paid practice test to assess your skills. There are also free tests on Udemy and other platforms. Take several tests to identify weak areas for improvement.
Use Online Learning Resources
- Microsoft Learn has free tutorials and modules to build Azure AI skills.
- Udemy has affordable AI102 exam prep video courses.
- YouTube channels like Azure Academy offer free training.
Focus on Responsible AI Principles
Understanding responsible and ethical AI is essential for the exam. Study Microsoft’s principles like fairness, transparency, privacy, inclusiveness, reliability and safety.
With diligent preparation using these tips, you can pass the AI102 exam and become a certified Microsoft Azure AI Engineer. The certification validates valuable skills for building advanced AI solutions on Microsoft’s trusted cloud platform.
AI102: Who Is An Azure AI Engineer?
An Azure AI Engineer is a professional who builds, manages, and deploys artificial intelligence (AI) solutions leveraging Microsoft Azure services. Their key responsibilities include:
Planning and Managing Azure AI Solutions
- Understanding business requirements and defining the scope and objectives for AI solutions on Azure
- Designing optimal architectures for AI solutions using Azure services like Cognitive Services, Bot Service, and Machine Learning
- Developing and executing testing strategies to ensure robust and scalable AI solution deployments
Implementing AI Capabilities
- Programming AI solutions using languages like Python and C#
- Integrating different Azure AI services like Computer Vision, Natural Language Processing, Conversational AI into applications
- Leveraging tools like Azure Machine Learning and Azure OpenAI to develop custom AI models
Monitoring and Optimizing AI Solutions
- Monitoring usage, performance metrics, and costs of Azure AI solutions
- Identifying and troubleshooting issues with AI solution deployments
- Continuously improving AI solutions by tuning hyperparameters and retraining models
Applying Responsible AI Principles
- Assessing AI systems for fairness, transparency, interpretability, and mitigation of harmful bias
- Documenting and communicating the limitations of AI solutions to stakeholders
- Understanding ethical implications of AI and developing solutions responsibly
The Azure AI Engineer Associate certification validates expertise across these responsibilities through passing the AI-102 exam. Preparing through study guides, practice tests, training courses, and hands-on experience with Azure AI services is key to becoming a certified Azure AI Engineer.
AI102: What Are The Prerequisites For The Exam?
Preparing for the AI-102 exam requires some key prerequisites and skills. Here are the main things you need before attempting the exam:
Programming Experience
- Hands-on experience with C# or Python programming is essential. You should be comfortable writing code in one of these languages.
- Understanding of common data structures, algorithms, and programming concepts like OOP will help with exam questions.
Azure and AI Fundamentals
- Solid foundational knowledge of Microsoft Azure and its main services. Key areas to focus on are:
- Azure Cognitive Services
- Azure Bot Service
- Azure Cognitive Search
- Understanding of core AI and machine learning concepts like natural language processing, computer vision, knowledge mining, etc.
Development Experience
- Practical expertise in developing AI solutions leveraging Azure. This includes:
- Consuming Azure Cognitive Services via SDKs and REST APIs
- Building bots using the Bot Framework
- Creating search indexes and configuring data sources
- Proficiency in using common dev tools like Visual Studio, Git, Azure Portal.
Responsible AI Principles
- Knowledge of responsible AI practices around fairness, transparency, privacy, and security.
Gaining hands-on development experience with Azure AI services is the best preparation. Trying sample projects and tutorials can significantly boost exam readiness. Overall, combining conceptual knowledge with practical skills is key to passing this advanced certification exam.
AI102: Salary And Career Path For An Azure AI Engineer
The AI102 exam focuses on designing and implementing Microsoft Azure AI solutions. It is one of the exams required for the Microsoft Certified: Azure AI Engineer Associate certification. This certification opens up lucrative career opportunities in one of the hottest fields in tech – artificial intelligence and machine learning.
Salary
According to Glassdoor, the average base salary for an Azure AI Engineer in the US is $132,000 per year. With total compensation going up to $158,000 including bonuses and stock options.
Career Path
An Azure AI Engineer typically works with data scientists, IoT specialists, and AI developers to build end-to-end AI solutions on the Microsoft Azure platform.
Some of the key responsibilities include:
- Collaborating with solution architects to understand requirements
- Implementing AI, machine learning and deep learning models
- Managing and monitoring AI solutions in production
- Performance tuning and optimization
- Ensuring responsible use of AI
Growth Prospects
The demand for AI skills is exploding. A report from Indeed shows a whopping 344% annual growth in AI job postings between 2015 and 2019. This growth is expected to continue well into the 2020s.
Major tech firms like Microsoft, Google, Amazon, and Facebook as well as startups are all investing heavily in AI. This is great news for Azure AI Engineers as it creates abundant job opportunities.
Getting Started
For those interested in becoming an Azure AI Engineer, here are some tips:
- Gain a basic understanding of cloud concepts
- Learn Python or C# programming
- Get familiar with common AI and data science frameworks like TensorFlow, PyTorch, scikit-learn etc.
- Study for and pass the AI102 exam
- Build out your portfolio with AI/ML projects
- Learn tools like Git, Docker, Kubernetes that are used to build and deploy AI applications
With some dedicated effort, passing the AI102 and becoming a certified Azure AI Engineer is a very viable goal for software engineers and data scientists looking to level up into an exciting career integrating AI into business solutions on the cloud.
AI102: Benefits of The Certification
The AI-102 certification focuses on designing and implementing Microsoft Azure AI solutions. It demonstrates proficiency in leveraging Azure’s cognitive services for natural language processing, computer vision, knowledge mining, and conversational AI. Obtaining this certification can provide several key benefits for one’s career:
Enhanced Employability
The AI-102 certification validates expertise in an in-demand skillset. As more companies adopt AI, there is a growing need for professionals who can effectively build and deploy AI solutions on Azure. Having this certification on your resume can make you more competitive for roles like Azure AI Engineer, Machine Learning Engineer, Data Scientist, and more.
Higher Salaries
Certified professionals typically command higher salaries than those without credentials. One survey found that IT professionals with Azure certifications earn over $12,000 more on average per year. The AI-102 specifically focuses on an advanced, specialized skillset that is likely to attract increased compensation.
Career Advancement
The certification demonstrates up-to-date skills in a rapidly advancing field. It shows you have put in the work to stay current and can apply the latest AI methods on Azure. This can set you apart for leadership roles and projects involving AI implementation.
Gaining New Skills
Preparing for the exam requires hands-on practice across Azure Cognitive Services. You will build knowledge of services like Language, Speech, Vision, Search and more. These skills will serve you well on-the-job when developing real-world AI solutions.
AI102: How To Prepare For The Exam
The AI102 exam tests your skills in designing and implementing Microsoft Azure AI solutions. Proper preparation is key to passing this challenging exam. Here are some tips on how to effectively get ready:
Understand the exam objectives
The first step is to thoroughly review the AI102 exam page and identify the topics you need to focus on. The exam measures skills in:
- Planning and managing Azure AI solutions (15-20%)
- Implementing decision support solutions (10-15%)
- Implementing computer vision solutions (15-20%)
- Implementing natural language processing solutions (15-20%)
- Implementing knowledge mining and document intelligence solutions (10–15%)
- Implementing generative AI solutions (10–15%)
Use official study resources
Microsoft provides useful free study resources including:
- AI102 study guide
- AI102 exam prep videos
- Practice questions
Going through these will familiarize you with the exam format, question styles, and key topic areas.
Get hands-on experience
Nothing beats actually building and deploying solutions using Azure AI services. Get practice with:
- Azure Cognitive Services
- Azure Cognitive Search
- Microsoft Bot Framework
Aim to create solutions leveraging computer vision, NLP, decision support, knowledge mining, and generative AI.
Take practice tests
Finally, take mock exams to test your knowledge. Time yourself to get used to the actual exam pace. Review missed questions in detail.
Adequate preparation and hands-on experience are vital for passing the AI-102 certification exam. Use a combination of Microsoft’s official study resources, your own Azure AI projects, and practice tests to get exam-ready.
Conclusion: Preparing for Success on the AI102 Exam
Passing the AI102 exam requires dedication and hard work. By studying the exam objectives, leveraging Microsoft’s official learning resources, gaining hands-on experience, and taking practice tests, you can fully prepare.
Gaining this certification is within your reach with disciplined preparation. By learning from Microsoft’s subject matter experts and earning the AI102 credential, you can establish yourself as an authority in applying Artificial Intelligence on the trusted Azure platform.
