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Top Microsoft Azure Courses to Boost Your AI Skills

Artificial Intelligence (AI) is rapidly transforming the world, and Microsoft Azure is at the forefront of this revolution. If you're looking to upskill or launch a career in AI, Microsoft offers a comprehensive range of courses designed to equip you with the knowledge and expertise you need to succeed. Whether you're a complete beginner or an experienced developer, a Microsoft Azure AI course is perfect for your learning goals.


Top Microsoft Azure Courses to Boost Your AI Skills

This article explores some of the most popular and valuable Microsoft Azure AI courses, categorized to guide your AI learning journey.


Top Microsoft Azure Courses to Boost Your AI Skills


Course 1: Microsoft Azure Machine Learning

Level: Beginner Level

Duration: 11 hours


The Microsoft Azure Machine Learning course sets you on the path to conquering the Microsoft Azure AI Fundamentals exam (AI-900). Gain a solid understanding of core AI concepts relevant to the exam. This course specifically targets the skills and knowledge areas assessed in the AI Fundamentals exam domains. Get practical experience working with Microsoft Azure, even if you're new to the platform.



This course covers the following:

  • Gain a solid grasp of core machine learning concepts, including different types of machine learning models and their purposes.

  • Explore the key tasks in creating a Machine learning solution, from conceptualization to deployment.

  • Discover the power of Azure Machine Learning Studio, a user-friendly interface that allows you to build machine learning models without extensive coding.


You will get 12 quizzes to test your understanding of the concepts presented.


There are 4 modules in this course:

  1. Automated Machine Learning Power:  Learn how to identify different types of machine learning models and leverage Azure Machine Learning's automation features. This module equips you to train and deploy a powerful predictive model without extensive coding.

  2. Building Regression Models Visually:  This module delves into creating regression models for predicting future values based on historical data. You'll learn how to build these models using the user-friendly Azure Machine Learning designer interface.

  3. Classification Models Made Easy:  Classification models categorize things into groups. In this module, you'll discover how to build classification models using the Azure Machine Learning Designer, again focusing on a visual approach.

  4. Unsupervised Learning with Clustering:  Clustering models help identify groups (or clusters) within data sharing similar characteristics. This module guides you through creating clustering models using the familiar Azure Machine Learning designer interface.


Course 2: Artificial Intelligence on Microsoft Azure

Level: Beginner Level

Duration: 3 hours


The Artificial Intelligence on Microsoft Azure course will show you how Microsoft Azure, a cloud platform, can be used to create powerful AI solutions. AI is revolutionizing how we solve problems, analyze data, and interact with the world around us.


Discover how AI is being used to tackle all sorts of challenges, from medical diagnosis to weather prediction. AI can analyze massive amounts of data, make super accurate guesses (predictions), and even automate tasks in amazing ways.


The course will emphasize how important it is to build AI that's fair and unbiased, meaning it treats everyone equally. We also need to understand how AI makes decisions and keeps user data safe and secure.



This course covers the following:

  • Explore the core concepts of AI, including machine learning, anomaly detection, computer vision, natural language processing, and conversational AI.

  • Discover the various ways AI can be utilized and the different types of AI workloads supported by Microsoft Azure.

  • Learn about the importance of responsible AI development and ethical considerations when building AI solutions.


The course includes 6 quizzes to assess your understanding of the key concepts covered throughout the material.


Course 3: Microsoft Cybersecurity Analyst

Level: Beginners Level

Duration: 6 months | 10 hours a week


This comprehensive Cybersecurity Analyst program equips you with the knowledge and practical skills needed to thrive in today's ever-evolving cyber threat landscape. Designed for beginners, this program takes you on a journey from core cybersecurity concepts to real-world applications within a business environment.


Learn how cybersecurity concepts translate into practical strategies to protect your organization's data and infrastructure. Develop a comprehensive understanding of cyber threats and explore effective mitigation strategies from an enterprise perspective.


Apply your learnings within a simulated Azure environment, gaining practical experience with industry-standard tools like Microsoft Defender and Azure Active Directory.

Graduate with a portfolio of tangible examples to showcase your skills and impress potential employers during interviews.



This course covers the following:

  • Gain a solid understanding of the cybersecurity landscape, core security concepts, compliance requirements, and identity solutions.

  • Learn how to identify vulnerabilities within an organization's network and implement strategies to mitigate cyberattacks and protect sensitive data.

  • Develop and implement effective cybersecurity measures within the Azure environment to proactively defend against evolving cyber threats.

  • Demonstrate your newfound knowledge and skills through a culminating capstone project, preparing you for real-world challenges.

  • Prepare for the industry-recognized Microsoft SC-900 exam, validating your understanding of core security, compliance, and identity concepts.


This program is comprised of 9 progressive courses, building your knowledge step-by-step:

  • Introduction to Computers and Operating Systems and Security: This foundational course introduces you to computer systems, operating systems, and the basics of cybersecurity.

  • Introduction to Networking and Cloud Computing: Learn how to set up cloud environments, virtual machines, and network infrastructure while exploring network security concepts.

  • Cybersecurity Threat Vectors and Mitigation: Gain a comprehensive understanding of cyber threats, vulnerabilities, encryption methods, and key security/compliance concepts.

  • Cybersecurity Identity and Access Solutions using Azure AD: This course dives deeper into securing identities and access using Azure Active Directory (Azure AD).

  • Cybersecurity Solutions and Microsoft Defender: Explore various cloud security policies and tools like Microsoft Defender for Cloud, Security Information and Event Management (SIEM), and Security Orchestration, Automation, and Response (SOAR).

  • Cybersecurity Tools and Technologies: Learn to utilize security testing tools within a cloud environment, including penetration testing and planning.

  • Cybersecurity Management and Compliance: Explore data management, information security, compliance frameworks, and tools for managing compliance effectively.

  • Advanced Cybersecurity Concepts and Capstone Project: Develop strategies to manage cyber risks, mitigate threats, and protect data. You'll also complete a capstone project to solidify your learning.

  • Microsoft SC-900 Exam Preparation and Practice: This final course focuses on preparing you for the Microsoft SC-900 exam. You'll gain in-depth knowledge of core security, compliance, and identity concepts tested on the exam.


Course 4: Microsoft Azure Data Scientist Associate (DP-100)

Level: Intermediate Level

Duration: 2 months | 10 hours a week


This Professional Certificate program is designed for experienced data scientists who want to take their skills to the cloud using Microsoft Azure. If you know Python and Machine learning frameworks like Scikit-Learn, PyTorch, and TensorFlow, this program is the perfect way to learn how to build and manage machine learning solutions on the Azure platform.


Learn the entire lifecycle of creating machine learning solutions in Azure, from managing resources to deployment and beyond. Discover how to leverage the power of Azure to manage resources, run experiments, train models, and operationalize your Machine learning solutions efficiently.


Develop best practices for building and deploying ethical and responsible machine learning solutions. Learn how to use Azure Databricks for data exploration, preparation, and modeling, seamlessly integrating it with Azure Machine Learning.



This course covers the following:

  • Become proficient in managing and optimizing Azure resources specifically for data science projects.

  • Learn how to conduct data experiments and effectively train various machine learning models.

  • Discover best practices for deploying and managing ethical Machine learning solutions in production environments.

  • Prepare yourself to earn the DP-100 certification, a valuable credential to validate your expertise in Azure data science.


This program is comprised of five individual courses that progressively build your knowledge and skills, culminating in exam preparation:

  • Create Machine Learning Models in Microsoft Azure: This course teaches you how to set up an Azure environment for data science and train various predictive models.

  • Microsoft Azure Machine Learning for Data Scientists: Explore different machine learning models, leverage Azure's automated machine learning capabilities, and build models using the Azure Machine Learning designer - all without extensive coding.

  • Build and Operate Machine Learning Solutions with Azure: Delve deeper into using the Azure Machine Learning Python SDK to create enterprise-grade ML solutions. You'll learn to work with data and computing resources, train models, deploy services, and ensure data security.

  • Perform Data Science with Azure Databricks: Learn Apache Spark on Azure Databricks to tackle large-scale data science workloads. This course equips you with skills for machine learning, user-defined functions (UDFs), DataFrames, Delta Lake creation and querying, and big data processing using notebooks.

  • Prepare for DP-100: Data Science on Microsoft Azure Exam: This final course focuses on exam preparation. You'll gain a comprehensive understanding of the key topics covered in the DP-100 exam, learn best practices for studying, and develop the proficiency to showcase your skills on the exam.


Course 5: Create Machine Learning Models in Microsoft Azure

Level: Intermediate Level

Duration: 12 hours


The Create Machine Learning Models in Microsoft Azure course equips you with the skills to excel in data science roles on Microsoft Azure. You'll learn everything you need to go from setting up your Azure environment to deploying powerful Machine learning models in production.


Learn how to plan and create a customized Azure environment specifically designed for data science workloads, optimizing your workflow for success. Discover best practices for running data experiments, allowing you to explore your data effectively and train Machine learning models.


Develop your skills in training a variety of predictive models, empowering you to make data-driven forecasts and uncover valuable insights. Learn how to effectively manage, optimize, and refine your machine learning models, ensuring they deliver the best possible results.



This course covers the following::

  • Learn how to set up and manage a data science environment on Microsoft Azure, optimizing your workflow for machine learning projects.

  • Discover techniques for running data experiments and training various types of machine learning models, including models for predicting numeric values, classification, clustering, and even deep learning.


There are 23 quizzes to test your understanding throughout the course.


The course is structured into 3 core modules:

  1. Explore Data and Create Models: This module gets you started with exploring data and building basic models to predict numeric values.

  2. Classification and Clustering: Dive deeper into training and evaluating models for classification tasks (sorting data into categories) and clustering tasks (identifying groups within data).

  3. Deep Learning Models: Explore the world of deep learning by learning how to train and evaluate deep learning models for complex tasks.


Course 6: Preparing for AI-900: Microsoft Azure AI Fundamentals exam

Level: Beginner Level

Duration: 9 hours


This comprehensive course is designed to be your ultimate review tool for the Microsoft Azure AI Fundamentals (AI-900) certification exam. This course provides the perfect opportunity to solidify your understanding of key concepts and boost your exam confidence.


Deepen your understanding of the features and functionalities of computer vision, Natural Language Processing (NLP), and conversational AI workloads within the Azure platform.



This course covers the following:

  • Refresh and test your understanding of key AI concepts covered in the AI-900 exam.

  • Develop the proficiency needed to demonstrate mastery of the skills measured in the Microsoft Azure AI Fundamentals exam.

  • Gain a solid grasp of the core concepts covered in the Microsoft Azure AI Fundamentals Specialization.

  • Learn best practices and effective strategies to ensure you're fully prepared for the exam.


There are 5 quizzes to test your understanding throughout the course.


The course is structured into 4 modules:

  • Prepare for AI-900: Microsoft Azure AI Fundamentals Exam: This introductory module sets the stage for your exam prep journey.

  • Exam Prep 1, 2, and 3: These modules delve deeper into the core exam topics, providing focused exam preparation.


Course 7: Data Analysis and Visualization with Power BI

Level: Beginners Level

Duration: 29 hours


This Power BI course will equip you with the skills to design and format impactful reports and dashboards. You'll explore data visualization, using Power BI's powerful tools to create clear and engaging presentations. The course will also teach you how to navigate reports effectively, guiding viewers through your data and uncovering its deeper meaning. Furthermore, you'll learn advanced analytics techniques to extract hidden patterns and trends and gain the expertise to create and export professional reports for easy sharing with stakeholders. By the end, you'll be empowered to transform raw data into compelling narratives, using Power BI to become a master data storyteller.



This course covers the following:

  • Discover how to use charts, graphs, and other visual elements to communicate data insights.

  • Learn how to create reports and dashboards that present information in a clear and organized way.

  • Understand how to design reports and dashboards accessible to everyone, regardless of their abilities.

  • Explore techniques for using visualizations to identify patterns, trends, and other important information within your data.

There are 21 quizzes and 6 assignments to test your understanding throughout the course.


The course is structured into 6 modules to guide you step-by-step:

  1. Creating Reports: This module gets you started with building basic reports in Power BI.

  2. Navigation and Accessibility: Learn how to design reports for everyone to navigate and understand.

  3. Bringing Data to the User: Discover how to present data in a way that is most effective for your audience.

  4. Identifying Patterns and Trends: Explore techniques for using visualizations to uncover hidden insights within your data.

  5. Guided Project: Apply your newfound skills in a guided project focused on data analysis and visualization with Power BI.

  6. Final Project and Assessment: Put your learning to the test by completing a final project that demonstrates your ability to create impactful data visualizations with Power BI.


Course 8: Microsoft Azure Machine Learning for Data Scientists

Level: Intermediate Level

Duration: 11 hours


The Microsoft Azure Machine Learning for Data Scientists course is a specialized program designed to propel your data science skills to the next level and prepare you to excel in the Microsoft Azure Data Scientist Associate (DP-100) certification exam. Leveraging your existing Python and machine learning expertise, this program equips you with the knowledge and tools to manage and operate machine learning solutions at a cloud scale using Microsoft Azure Machine Learning.


Learn how to manage the entire machine learning lifecycle in Azure, from data ingestion and preparation to model deployment and monitoring – all within a cloud environment.



This course will cover the following:

  • Learn about different types of machine learning models, including regression, classification, and clustering.

  • Discover how to utilize Azure Machine Learning's automated capabilities to train and deploy predictive models efficiently.

  • The course guides you through creating regression, classification, and clustering models using the user-friendly Azure Machine Learning Designer interface, eliminating the need for coding.


There are 12 quizzes to test your understanding throughout the course.


The course is structured into four modules:

  1. Using Automated Machine Learning in Azure Machine Learning: This module introduces you to Azure's automated machine learning features.

  2. Create a Regression Model with Azure Machine Learning Designer: Learn how to build a regression model visually using the Azure Machine Learning Designer.

  3. Create a Classification Model with Azure AI: This module dives into creating classification models with Azure AI, again leveraging the designer interface.

  4. Create a Clustering Model with Azure AI: The final module will focus on building clustering models using Azure AI's visual tools.


Course 9: Build and operate Machine Learning Solutions with Azure

Level: Intermediate Level

Duration: 31 hours


The Build and Operate Machine Learning Solutions with Azure course dives deep into using the Azure Machine Learning Python SDK, empowering you to build and manage robust machine learning solutions designed for enterprise use within the Microsoft Azure cloud platform. This focus on real-world applications aligns perfectly with the Microsoft Azure Data Scientist Associate (DP-100) certification exam.


Build and operate Machine Learning Solutions with Azure course will teach you how to build and run machine learning solutions using Microsoft Azure. It's designed for people with some experience in machine learning and Python.



There are 35 quizzes to test your understanding throughout the course.


This course covered the following:

  • Using the Azure Machine Learning Python SDK to create professional machine learning solutions.

  • Working with data and computing resources in Azure Machine Learning.

  • Training machine learning models using the Azure Machine Learning SDK, including choosing models and protecting sensitive data.

  • Building pipelines and deploying real-time machine learning services with Azure Machine Learning.


The course is broken down into 6 modules:

  1. Training Machine Learning Models: Learn how to use the Azure Machine Learning SDK to train models.

  2. Working with Data and Compute: Understand how to manage data and computing resources in Azure Machine Learning.

  3. Deploying Real-Time Services: Build pipelines to deploy machine learning models as real-time services.

  4. Batch Inference and Hyperparameter Tuning: Explore techniques for deploying batch inference pipelines and tuning model hyperparameters using Azure Machine Learning.

  5. Model Selection and Data Protection: Learn how to select appropriate machine learning models and protect sensitive data within your solutions.

  6. Monitoring Deployments: Discover how to monitor the performance of your deployed machine learning models.


Conclusion

So there you have it! These Microsoft Azure AI courses offer a great starting point for anyone looking to learn AI. From beginner basics to advanced certifications, there's something for everyone. Just pick a course that interests you and start your AI journey today!

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