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The AI-102: Designing and Implementing a Microsoft Azure AI Solution certification exam tests the candidate’s experience and knowledge of the AI solutions that make the most of Azure Cognitive Services and Azure services. In addition, the exam also tests the candidate's ability to implement this knowledge by participating in all phases of AI solutions development—from defining requirements, and design to development, deployment, integration, maintenance, performance tuning, and monitoring.

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The AI-102: Designing and Implementing a Microsoft Azure AI Solution certification exam tests the candidate’s experience and knowledge of the AI solutions that make the most of Azure Cognitive Services and Azure services. In addition, the exam also tests the candidate's ability to implement this knowledge by participating in all phases of AI solutions development—from defining requirements, and design to development, deployment, integration, maintenance, performance tuning, and monitoring.

Take this Designing and Implementing a Microsoft Azure AI Solution: AI-102 exam and become a part of the futuristic world of Artificial Intelligence and grow your career by attaining Azure AI-102 certification.

Azure AI engineers have experience developing solutions that use languages such as Python or C# and should be able to use REST-based APIs and software development kits (SDKs) to build secure image processing, video processing, natural language processing (NLP), knowledge mining, and conversational AI solutions on Azure. They should be familiar with all methods of implementing AI solutions. Plus, they understand the components that make up the Azure AI portfolio and the available data storage options. Azure AI engineers also need to understand and be able to apply responsible AI principles.

This course contains 5+ hours of training videos. Learners could find a total of 90+ lectures in the training course with comprehensive coverage of all topics regarding the exam AI-102: Designing and Implementing a Microsoft Azure AI Solution. These lectures are divided into 5 Modules and each module is further split into lessons. The entire course includes Assessments to validate knowledge checks of learners. Also, a set of Graded Questions is available at the end of every module.

Module 1: Azure AI Solutions: Planning and Management

Module 2: Image & Video Processing Solutions

Module 3: Natural Language Processing (NLP) Solutions

Module 4: Knowledge Mining Solutions

Module 5: Conversational AI Solutions

Enroll in Exam Prep AI-102: Microsoft Azure AI Engineer Associate Course and advance your Azure AI Solution Workload skills with Microsoft Azure.

This training course helps you develop your skills and knowledge in AI-102. You can start with fundamental certifications such as the AI-900 exam. Once you gain command over all phases of AI solutions development, you are ready to start preparing for the AI-102 exam.

This AI-102 course is mainly for those who need opportunities in various job roles such as Cloud Developers, Cloud Engineers, Solutions Architects, and Cloud Architects.

By the end of this course, you will be able to pass the AI-102 exam on the first attempt and master Designing and Implementing a Microsoft Azure AI Solution.

Enroll now

What's inside

Syllabus

Azure AI solutions: Planning and Management
Welcome to Week 1 of the Course. In this week, we’ll explore the basic course introduction and Azure Congitive Services. We will also explore the the concepts of Azure AI services with security based selecion. By the end of the course we'll learn how to create solutions to detect anomalies and improve content.
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Image & Video Processing Solutions
Welcome to Week 2 of the Course. This week, we’ll explore the concepts of Image processing requirements, responses, and features. We learn the concepts of Text Extractor and Azure Video Indexer. By the end of this course, we will be able to configure Image classification and object detection in Azure AI Services.
Natural Language Processing (NLP) Solutions
Welcome to Week 3 of the Course. This week, we’ll explore the concepts of Analyzing text & Process Speech. We will learn the concepts of the Translate Language & Language Understanding Model. By the end of this course, we will be able to create Conversational Q&A solutions in Azure AI Services.
Knowledge Mining Solutions
Welcome to Week 4 of the Course. This week, we’ll explore the concepts of Cognitive Search & AI Enrichment Skills. Then we learn how to perform Query an index, including syntax, sorting, filtering, and wildcards. By the end of this course, we will learn to demonstrate indexing by adding Cognitive Skills concepts.
Conversational AI Solutions
Welcome to the final week(Week 5) of the Course. This week, we’ll explore the concepts of AI Conversation Flow and Cognitive Search Solutions. Then we will learn how to analyze the concepts of Testing and Publishing the Conversational Bot. By the end of this course, we will be able to learn how to build, test and publish a Conversational Bot in Azure AI Services.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Examines Microsoft Azure as a cloud computing platform for developing, deploying, maintaining, and managing AI solutions
Provides comprehensive knowledge on the Azure AI services, including image processing, video processing, natural language processing, knowledge mining, and conversational AI solutions
Covers industry-standard best practices and techniques for designing and implementing AI solutions on Microsoft Azure
Requires students to pass the AI-102 certification exam to demonstrate their understanding and skills in designing and implementing Microsoft Azure AI solutions
Assumes students have a foundational understanding of AI concepts, as well as proficiency in Python or C# programming languages
Provides practical experience through hands-on labs and real-world case studies, enhancing students' ability to apply their knowledge and skills in real-world scenarios

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Exam Prep AI-102: Microsoft Azure AI Engineer Associate with these activities:
Online Tutorial: Introduction to NLP
Review the basics of NLP to strengthen your foundational knowledge before starting the course.
Show steps
  • Enroll in an online tutorial or course on NLP fundamentals.
  • Complete the tutorial, focusing on concepts like text mining, language models, and sentiment analysis.
  • Practice using NLP techniques through hands-on exercises.
Attend a Webinar on Azure AI Best Practices
Participate in a webinar led by industry experts to gain insights into best practices in Azure AI development.
Browse courses on Azure AI Solutions
Show steps
  • Find and register for a webinar hosted by Microsoft or other reputable organizations.
  • Attend the webinar and actively engage with the presenters.
  • Take notes on key takeaways and best practices discussed during the webinar.
Practice Azure AI Service REST APIs
Practicing REST APIs will help you understand how to interact with Azure AI services and build solutions that leverage their capabilities effectively.
Browse courses on REST APIs
Show steps
  • Review the Azure AI documentation for the REST API you want to use.
  • Create a development environment and install the necessary tools.
  • Write code to call the REST API and handle the responses.
Two other activities
Expand to see all activities and additional details
Show all five activities
Coding Challenges in Azure
Engage in hands-on practice to reinforce your understanding of Azure AI development.
Browse courses on Azure Cognitive Services
Show steps
  • Find coding challenges related to Azure Cognitive Services, such as image recognition or text analysis.
  • Attempt to solve the challenges using your knowledge of Azure AI tools and techniques.
  • Review your solutions and identify areas for improvement.
  • Seek feedback from experienced Azure AI engineers or online forums.
AI Blog Post
Create a blog post that demonstrates your understanding of a specific Azure AI solution.
Browse courses on Azure AI Solutions
Show steps
  • Choose an Azure AI solution that interests you, such as image processing or language understanding.
  • Research the solution and gather relevant information.
  • Write a comprehensive blog post that explains the solution, its benefits, and how to implement it.
  • Publish your blog post and share it with the community for feedback.

Career center

Learners who complete Exam Prep AI-102: Microsoft Azure AI Engineer Associate will develop knowledge and skills that may be useful to these careers:
AI Engineer
AI Engineers design, develop, and deploy artificial intelligence systems. They work with a variety of technologies, including machine learning, deep learning, and natural language processing. The AI-102 course can help prepare you for this career by teaching you the basics of AI, as well as how to use Microsoft Azure to develop and deploy AI systems.
Machine Learning Scientist
Machine Learning Scientists research and develop new machine learning algorithms and techniques. They work with a variety of data sources, including Microsoft Azure. The AI-102 course can help prepare you for this career by teaching you the basics of machine learning, as well as how to use Microsoft Azure to develop and deploy machine learning models.
Machine Learning Engineer
Machine Learning Engineers design and develop machine learning models that can be used to solve real-world problems. The AI-102 course can help prepare you for this career by teaching you the basics of machine learning, as well as how to use Microsoft Azure to develop and deploy machine learning models.
Data Engineer
Data Engineers design, build, and maintain data pipelines. They work with a variety of data sources, including Microsoft Azure. The AI-102 course can help prepare you for this career by teaching you the basics of data engineering, as well as how to use Microsoft Azure to design, build, and maintain data pipelines.
Data Scientist
Data Scientists use data to solve business problems. They collect, clean, and analyze data to identify patterns and trends. The AI-102 course can help prepare you for this career by teaching you the basics of data science, as well as how to use Microsoft Azure to collect, clean, and analyze data.
Cloud Architect
Cloud Architects design and manage cloud computing systems. They work with a variety of cloud technologies, including Microsoft Azure. The AI-102 course can help prepare you for this career by teaching you the basics of cloud computing, as well as how to use Microsoft Azure to design and manage cloud computing systems.
Data Analyst
Data Analysts collect, clean, and analyze data to identify patterns and trends. They use this information to help businesses make informed decisions. The AI-102 course can help prepare you for this career by teaching you the basics of data analysis, as well as how to use Microsoft Azure to collect, clean, and analyze data.
Solutions Architect
Solutions Architects design and implement technology solutions for businesses. They work with a variety of technologies, including Microsoft Azure. The AI-102 course can help prepare you for this career by teaching you the basics of technology solutions, as well as how to use Microsoft Azure to design and implement technology solutions.
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make informed decisions. They work with a variety of data sources, including Microsoft Azure. The AI-102 course can help prepare you for this career by teaching you the basics of business intelligence, as well as how to use Microsoft Azure to collect, clean, and analyze data.
Software Engineer
Software Engineers design, develop, and test software applications. They work with a variety of programming languages and technologies. The AI-102 course can help prepare you for this career by teaching you the basics of software engineering, as well as how to use Microsoft Azure to develop and deploy software applications.
Actuary
Actuaries use mathematical and statistical models to assess risk. They work with a variety of data sources, including Microsoft Azure. The AI-102 course may be useful to you as an Actuary by teaching you the basics of data analysis, as well as how to use Microsoft Azure to collect, clean, and analyze data.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. They work with a variety of data sources, including Microsoft Azure. The AI-102 course may be useful to you as an Operations Research Analyst by teaching you the basics of data analysis, as well as how to use Microsoft Azure to collect, clean, and analyze data.
Research Scientist
Research Scientists conduct research in a variety of fields, including artificial intelligence. They use a variety of data sources, including Microsoft Azure. The AI-102 course may be useful to you as a Research Scientist by teaching you the basics of AI, as well as how to use Microsoft Azure to develop and deploy AI systems.
University Professor
University Professors teach and conduct research in a variety of fields, including artificial intelligence. They use a variety of data sources, including Microsoft Azure. The AI-102 course may be useful to you as a University Professor by teaching you the basics of AI, as well as how to use Microsoft Azure to develop and deploy AI systems.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. They work with a variety of data sources, including Microsoft Azure. The AI-102 course may be useful to you as a Quantitative Analyst by teaching you the basics of data analysis, as well as how to use Microsoft Azure to collect, clean, and analyze data.

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Exam Prep AI-102: Microsoft Azure AI Engineer Associate.
A classic textbook on pattern recognition and machine learning, providing a comprehensive overview of the field. A valuable reference for those interested in the theoretical foundations of AI.
Examines the potential risks and benefits of developing artificial general intelligence (AGI), and considers the implications for humanity. A thought-provoking read for those interested in the long-term future of AI.
Covers statistical learning methods and their applications in machine learning. A valuable resource for those interested in the statistical foundations of AI and machine learning.
Covers deep learning concepts and techniques, using Python as the programming language. Provides a theoretical foundation for understanding AI and machine learning.
Provides an introduction to reinforcement learning, a type of machine learning where agents learn through interactions with their environment. Valuable for those interested in advanced AI techniques.
Provides a practical guide to data science, covering the challenges and pitfalls of real-world data analysis projects. Offers valuable insights for those interested in the practical aspects of AI and data science.
A comprehensive guide to AI concepts and techniques, using Python for implementation. Provides a broad overview of AI and its applications.

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