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Clint Bonnett

Hello, Cloud Gurus, and welcome to AI-900: Microsoft Certified Azure AI Fundamentals! Throughout this course, we’ll explore artificial intelligence and prepare you for the AI-900 certification exam in several ways. First, we’ll break down each section of the exam and take a look at their various components ranging from machine learning to image examination and language processing. From there, you’ll have a chance to get hands-on with a variety of labs designed to help reinforce what we’re learning in that section! Upon completion of the course, you’ll have a good understanding of artificial intelligence on Azure and be prepared to take the AI-900 exam! To be successful in this course, you should have 0-6 months of Azure experience and a basic understanding of cloud concepts. Don’t worry if you haven’t worked with code before, as the labs in this course are designed to require no coding skills. We hope to see you in the course, Gurus!

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Well-suited for those preparing for the AI-900 certification exam
Provides a hands-on approach through labs to reinforce concepts
Appropriate for beginners with limited Azure experience and no coding skills

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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 AI-900: Microsoft Certified Azure AI Fundamentals with these activities:
Review cloud computing concepts
Ensure a strong foundation for the course by reviewing essential cloud computing concepts, ensuring a better understanding of Azure AI services and capabilities.
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  • Identify key cloud computing concepts
  • Read articles and watch videos
  • Take practice quizzes or complete exercises
Complete practice questions
Enhance exam preparedness and reinforce course concepts by regularly completing practice questions related to AI-900 exam topics.
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  • Identify practice question resources
  • Set a schedule for practice
  • Review and analyze results
Practice with Azure ML Notebooks
Improve coding skills and strengthen understanding of ML Notebooks by completing guided tutorials within the Azure environment.
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  • Find tutorials and set up your environment
  • Follow tutorials and complete exercises
  • Share your findings and discuss with others
Four other activities
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Create a machine learning model
Strengthen understanding of machine learning model creation by developing a model using the skills and knowledge learned from this course.
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  • Define the problem and gather data
  • Choose and train a model
  • Evaluate and deploy the model
Develop a case study or solution brief
Demonstrate a deeper understanding of AI-900 concepts by creating a case study or solution brief that applies the principles and technologies learned in the course to a real-world business scenario.
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  • Identify a business problem or opportunity
  • Research and gather information
  • Develop a solution proposal using AI-900 principles
  • Create a presentation or document outlining the case study or solution brief
Attend AI-900 certification workshop
Gain in-depth knowledge and practical guidance on AI-900 exam topics by attending a comprehensive certification workshop.
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  • Research and find a reputable workshop
  • Enroll and attend the workshop
  • Actively participate and engage with instructors
  • Review workshop materials and practice exercises
Tutor or assist students with AI-900 concepts
Strengthen understanding of AI-900 concepts by sharing your knowledge and assisting other learners, both reinforcing your own learning and helping others succeed.
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  • Offer tutoring or assistance to classmates or online communities
  • Prepare and review course materials
  • Answer questions and provide guidance
  • Reflect on your own understanding and identify areas for improvement

Career center

Learners who complete AI-900: Microsoft Certified Azure AI Fundamentals will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts are responsible for extracting insights from data to support decision-making. This course provides a foundation in the fundamentals of Azure AI, including machine learning, image recognition, and natural language processing. By gaining these skills, learners can enhance their ability to analyze and interpret data, identify trends, and communicate insights to stakeholders. This course is highly recommended for aspiring and current Data Analysts seeking to leverage AI technologies to excel in their roles.
Data Scientist
Data Scientists are at the forefront of developing and implementing artificial intelligence solutions. By mastering the fundamentals of Azure AI, as taught in this course, learners will enhance their ability to model and interpret data, build and deploy machine learning models, and interpret the results to drive informed decision-making. This course provides a solid foundation for aspiring and current Data Scientists looking to advance their careers in the AI domain.
Machine Learning Engineer
Machine Learning Engineers play a pivotal role in designing, developing, and deploying machine learning systems. This course equips learners with the knowledge and skills necessary to build and maintain machine learning solutions on Azure. Through hands-on labs, they will gain experience in data preparation, model training, and model deployment. By completing this course, learners will be well-positioned to pursue a career as a Machine Learning Engineer and contribute to the development of cutting-edge AI applications.
AI Engineer
AI Engineers are highly specialized professionals who design, develop, and maintain AI systems. This course provides a solid foundation in the core concepts of Azure AI, including machine learning, computer vision, and natural language processing. Through hands-on labs, learners will gain experience in building and deploying AI solutions on Azure. This course is tailored for individuals aspiring to become AI Engineers or advance their careers in AI development.
Cloud Architect
Cloud Architects are responsible for designing, building, and managing cloud-based solutions. This course provides a comprehensive overview of Azure AI services and their applications. By understanding how to leverage AI capabilities on Azure, learners can design and implement cloud architectures that are intelligent, scalable, and secure. This course is ideal for Cloud Architects who want to expand their expertise in AI and drive innovation within their organizations.
Software Engineer
Software Engineers responsible for developing and maintaining software applications can benefit from this course by gaining a foundational understanding of Azure AI services. By incorporating AI capabilities into their applications, learners can enhance their functionality, improve user experience, and drive innovation. This course provides a practical approach to integrating Azure AI into software development, making it valuable for Software Engineers looking to stay ahead in the rapidly evolving tech landscape.
Business Analyst
Business Analysts play a crucial role in bridging the gap between business requirements and technical solutions. This course provides Business Analysts with an understanding of the potential of Azure AI in driving business value. By learning about machine learning, image recognition, and natural language processing, learners can effectively collaborate with technical teams to design and implement AI-powered solutions that meet business objectives.
Project Manager
Project Managers responsible for overseeing AI projects can benefit from this course by gaining a comprehensive understanding of Azure AI services and their applications. By learning about the capabilities and limitations of AI technologies, learners can effectively plan, execute, and deliver AI projects that meet stakeholder expectations. This course provides Project Managers with the knowledge and skills to navigate the complexities of AI development and ensure project success.
IT Manager
IT Managers responsible for overseeing IT infrastructure and services can benefit from this course by gaining a foundational understanding of Azure AI services. By learning about the potential of AI in IT operations, learners can make informed decisions about adopting AI solutions to improve efficiency, reduce costs, and enhance security. This course provides IT Managers with the knowledge and skills to evaluate, implement, and manage Azure AI services within their IT environments.
Data Engineer
Data Engineers are responsible for designing, building, and maintaining data pipelines and infrastructure. This course provides Data Engineers with an overview of Azure AI services and their role in data management. By understanding how to leverage AI capabilities for data processing, transformation, and analysis, learners can build more efficient and intelligent data pipelines. This course may be beneficial for Data Engineers looking to expand their skillset and contribute to the development of AI-driven data solutions.
Product Manager
Product Managers responsible for developing and managing AI-powered products can benefit from this course by gaining a comprehensive understanding of Azure AI services and their applications. By learning about the capabilities and limitations of AI technologies, learners can effectively design and deliver AI products that meet market needs. This course provides Product Managers with the knowledge and skills to navigate the complexities of AI development and ensure product success.
Technical Writer
Technical Writers responsible for documenting AI technologies and solutions can benefit from this course by gaining a foundational understanding of Azure AI services. By learning about the capabilities and limitations of AI technologies, learners can effectively create clear and concise technical documentation that supports users and developers. This course provides Technical Writers with the knowledge and skills to translate complex AI concepts into accessible language, ensuring the successful adoption and utilization of AI solutions.
Sales Engineer
Sales Engineers responsible for selling AI solutions can benefit from this course by gaining a comprehensive understanding of Azure AI services and their applications. By learning about the capabilities and benefits of AI technologies, learners can effectively communicate the value proposition of AI solutions to potential customers. This course provides Sales Engineers with the knowledge and skills to identify customer needs, demonstrate AI solutions, and overcome objections.
Customer Success Manager
Customer Success Managers responsible for supporting customers using AI solutions can benefit from this course by gaining a foundational understanding of Azure AI services. By learning about the capabilities and limitations of AI technologies, learners can effectively assist customers in implementing, using, and troubleshooting AI solutions. This course provides Customer Success Managers with the knowledge and skills to build strong customer relationships, ensure customer satisfaction, and drive adoption of AI solutions.
Marketing Manager
Marketing Managers responsible for developing and executing marketing campaigns for AI products and services can benefit from this course by gaining a foundational understanding of Azure AI services. By learning about the capabilities and benefits of AI technologies, learners can effectively create and deliver marketing campaigns that resonate with target audiences. This course provides Marketing Managers with the knowledge and skills to position AI solutions as valuable and desirable, driving demand and increasing market share.

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 AI-900: Microsoft Certified Azure AI Fundamentals.
Provides a practical guide to using OpenCV, an open-source library for computer vision. It covers topics such as image processing, object detection, and facial recognition, making it a valuable resource for those interested in exploring computer vision applications.
Provides a comprehensive guide to using TensorFlow, an open-source library for deep learning. It covers topics such as building and training neural networks, working with data, and deploying models, making it a valuable resource for those who want to gain practical experience with TensorFlow.
Provides a comprehensive overview of machine learning using Python, covering topics such as data preprocessing, feature engineering, and model evaluation. It valuable resource for those who want to learn how to apply ML techniques to real-world problems using Python.
Provides a comprehensive guide to building and deploying ML systems using Python. It covers topics such as data engineering, model training, and model evaluation, making it a valuable resource for those who want to learn how to develop end-to-end ML solutions.
Provides a practical guide to building and deploying deep learning models. It covers topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks, making it a valuable resource for those who want to gain hands-on experience with deep learning architectures.
Provides a comprehensive introduction to natural language processing (NLP), covering topics such as text classification, sentiment analysis, and machine translation. It useful resource for those who want to gain a solid understanding of NLP techniques and their applications.
Provides a gentle introduction to data science, covering topics such as data cleaning, data visualization, and machine learning. It valuable resource for those who are new to data science and want to learn the basics.
Delves into the core concepts of deep learning, providing a comprehensive overview of the field. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks, making it a valuable resource for those interested in exploring deep learning in more depth.
Provides a comprehensive overview of the mathematical foundations of machine learning, covering topics such as linear algebra, probability theory, and optimization. It valuable resource for those who want to gain a deeper understanding of the theoretical underpinnings of ML.

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