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Preparing for AI-900

Microsoft Azure AI Fundamentals exam

Microsoft

Microsoft certifications give you a professional advantage by providing globally recognized and industry-endorsed evidence of mastering skills in digital and cloud businesses.​​ In this course, you will prepare to take the AI-900 Microsoft Azure AI Fundamentals certification exam.

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Microsoft certifications give you a professional advantage by providing globally recognized and industry-endorsed evidence of mastering skills in digital and cloud businesses.​​ In this course, you will prepare to take the AI-900 Microsoft Azure AI Fundamentals certification exam.

You will refresh your knowledge of fundamental principles of machine learning on Microsoft Azure. You will go back over the main consideration of AI workloads and the features of computer vision, Natural Language Processing (NLP), and conversational AI workloads on Azure. In short, you will recap all the core concepts and skills that are measured by the exam.

You will test your knowledge in a series of practice exams​ mapped to all the main topics covered in the AI-900 exam, ensuring you’re well prepared for certification success. You will prepare to pass the certification exam by taking practice tests with similar formats and content.

You will also get a more detailed overview of the Microsoft certification program and where you can go next in your career. You’ll also get tips and tricks, testing strategies, useful resources, and information on how to sign up for the AI-900 proctored exam. By the end of this course, you will be ready to sign-up for and take the AZ-900 exam.​

This course is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience is not required; however, some general programming knowledge or experience would be beneficial. To be successful in this course, you need to have basic computer literacy and proficiency in the English language. You should be familiar with basic computing concepts and terminology, general technology concepts, including concepts of machine learning and artificial intelligence.

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What's inside

Syllabus

Prepare for the AI-900: Microsoft Azure AI Fundamentals exam
In this module, you’ll also have access to resources that will help you to prepare for the proctored exam, enhance your study techniques, and help develop successful exam strategies. You will have an opportunity to explore some other Microsoft certifications paths that can help to advance your career.
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Exam Prep 1
In this module, you will have an opportunity to recap some of the key points from Courses 1 & 2 of the Microsoft AI-900 AI Fundamentals Specialization and take a practice exam that covers the related skills measured in the AI-900 certification exam.
Exam prep 2
In this module, you will have an opportunity to recap some of the key points from Courses 3 & 4 of the Microsoft AI-900 AI Fundamentals Specialization and take a practice exam that covers the related skills measured in the AI-900 certification exam.
Exam prep 3
In this module, you will take a practice exam that covers the skills measured in the Exam AI-900: Microsoft Azure AI Fundamentals.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Appropriate for non-technical backgrounds
Covers foundational principles and applications of AI in Azure
Well-structured with practice exams and resources for exam preparation
Provides career guidance and exploration of other Microsoft certifications
May require prior knowledge of basic computer literacy
Does not cover advanced concepts or hands-on implementation of AI models

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Reviews summary

Excellent resources for ai-900 exam prep

Learners say that preparing for the AI-900 exam with this course is excellent. Students have largely positive reviews for the course instructor, materials, and overall informative qualities. Most learners highly recommend this course to others also studying for the AI-900 exam.
The lecturer is detailed and good at explaining technical terms.
"the lecturer is detailed and good at explaining technical terms into simple ones"
Course is helpful for passing the AI-900 exam.
"I scored 900 in the exam because of the hands on experince this course provided."
"I am eager to express my sincere gratitude."
"This is the second course I've taken on your platform that has enabled me to pass Microsoft exams with flying colors."
Some exercises use outdated software versions.
"So many of the exercises on this course are out of date relative to the version of the software."
"Often you cannot follow the instructions because they are no longer relevant to the software."

Activities

Coming soon We're preparing activities for Preparing for AI-900: Microsoft Azure AI Fundamentals exam. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Preparing for AI-900: Microsoft Azure AI Fundamentals exam will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning models. They work with data scientists, software engineers, and other stakeholders to identify opportunities for using machine learning to solve business problems. This course helps build a foundation in machine learning principles and provides hands-on experience with Microsoft Azure AI tools, preparing you for success as a Machine Learning Engineer.
AI Engineer
An AI Engineer designs, develops, and deploys AI systems. They work with stakeholders to identify opportunities for using AI to solve business problems. This course helps build a foundation in AI principles and provides hands-on experience with Microsoft Azure AI tools, preparing you for success as an AI Engineer.
Data Analyst
A Data Analyst collects, cleans, and analyzes data to identify trends and patterns. They then use this information to develop insights and recommendations for business stakeholders. This course provides a foundation in machine learning and data analysis, preparing you for success as a Data Analyst.
Data Scientist
A Data Scientist uses data to solve business problems. They collect, clean, and analyze data to identify trends and patterns. They then use this information to develop predictive models and other data-driven insights. This course helps build a foundation in machine learning and data analysis, preparing you for success as a Data Scientist.
AI Researcher
An AI Researcher conducts research in the field of artificial intelligence. They develop new algorithms and techniques for solving complex problems. This course provides a foundation in AI principles and machine learning, which can be helpful for AI Researchers who want to stay up-to-date on the latest advances in the field.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. They work with stakeholders to understand requirements, and then use their technical skills to create software solutions. This course provides a foundation in machine learning and Azure AI tools, which can be helpful for Software Engineers who want to incorporate machine learning into their projects.
Technical Writer
A Technical Writer creates documentation for software and other technical products. They work with engineers and other technical experts to understand the product, and then write clear and concise documentation for users. This course provides a foundation in AI principles and machine learning, which can be helpful for Technical Writers who want to write documentation for AI products.
Educator
An Educator teaches students about a variety of subjects. They work with students to develop their knowledge and skills, and to prepare them for success in their careers. This course provides a foundation in AI principles and machine learning, which can be helpful for Educators who want to teach students about AI.
Sales Engineer
A Sales Engineer provides technical expertise to customers during the sales process. They work with sales teams to identify customer needs, and then use their technical skills to demonstrate how products can meet those needs. This course provides a foundation in AI principles and machine learning, which can be helpful for Sales Engineers who want to sell AI products.
Product Manager
A Product Manager manages the development and launch of new products. They work with stakeholders to understand requirements, and then use their technical and business skills to develop and launch successful products. This course provides a foundation in AI principles and machine learning, which can be helpful for Product Managers who want to incorporate AI into their products.
Project Manager
A Project Manager plans, executes, and closes projects. They work with stakeholders to define project scope, timelines, and budgets. This course provides a foundation in AI principles and machine learning, which can be helpful for Project Managers who want to incorporate AI into their projects.
Business Analyst
A Business Analyst analyzes business processes and identifies opportunities for improvement. They work with stakeholders to understand requirements, and then use their analytical skills to develop solutions. This course provides a foundation in AI principles and machine learning, which can be helpful for Business Analysts who want to incorporate AI into their projects.
Marketing Manager
A Marketing Manager develops and executes marketing campaigns. They work with stakeholders to define marketing goals, and then use their marketing skills to develop and execute campaigns that achieve those goals. This course provides a foundation in AI principles and machine learning, which can be helpful for Marketing Managers who want to incorporate AI into their marketing campaigns.
Consultant
A Consultant provides advice and guidance to clients on a variety of topics. They work with clients to understand their needs, and then use their expertise to develop and implement solutions. This course provides a foundation in AI principles and machine learning, which can be helpful for Consultants who want to advise clients on AI-related topics.
Cloud Architect
A Cloud Architect designs and manages cloud computing solutions. They work with stakeholders to understand requirements, and then use their technical skills to design and implement cloud solutions. This course provides a foundation in Azure AI tools, which can be helpful for Cloud Architects who want to incorporate AI into their cloud solutions.

Reading list

We've selected nine 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 Preparing for AI-900: Microsoft Azure AI Fundamentals exam.
Provides a practical introduction to machine learning using Python, covering essential concepts and techniques used in real-world applications. It complements the course by offering hands-on examples and exercises.
Offers a comprehensive overview of machine learning using Python. It covers a wide range of topics, from data preprocessing to model evaluation, providing a valuable reference for both beginners and experienced practitioners.
Provides a comprehensive overview of computer vision algorithms and their applications. It covers topics such as image formation, feature detection, and object recognition, offering a deeper understanding of the computer vision concepts tested in the AI-900 exam.
Provides a hands-on introduction to AI and machine learning for coders. It uses Python and TensorFlow to demonstrate essential concepts and techniques, offering practical examples that complement the theoretical aspects covered in the course.
Presents artificial intelligence algorithms in a clear and intuitive way, using visual representations and easy-to-understand explanations. It provides a good foundation for grasping the algorithmic concepts tested in the AI-900 exam.
Provides a comprehensive overview of Natural Language Processing (NLP) techniques using Python. It covers essential NLP concepts and algorithms, enhancing your understanding of the NLP aspects tested in the AI-900 exam.
Provides a visual introduction to deep learning, making it accessible to readers with limited mathematical background. It uses intuitive diagrams and examples to explain complex concepts, supporting the understanding of deep learning topics in the AI-900 exam.
For those interested in exploring deep learning, this book offers a comprehensive guide to building and training deep learning models using Python. It covers advanced topics that may be useful for further exploration beyond the AI-900 exam.
Introduces machine learning concepts in a simple and approachable manner, making it suitable for beginners with little background in the field. It provides a good starting point for those seeking a foundation before taking the AI-900 exam.

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