389+ certificates & courses
Microsoft certifications validate your skills in Azure, Office 365, Power Platform, and AI. Highly valued in enterprise IT roles across India.
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Microsoft (via Coursera) · Data Visualization
Microsoft Power BI Data Analyst Professional Certificate is a comprehensive beginner-level resource offered by Microsoft, focused on building practical skills in business and finance. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a professional certificate program designed to validate your skills for employers. The curriculum has been developed in collaboration with industry experts to ensure it covers exactly what hiring managers look for. Upon completion, you'll receive a shareable certificate that you can add to your LinkedIn profile, include in your resume, and present during job interviews. Many recruiters at Indian tech companies specifically look for these credentials when screening candidates. This resource covers topics essential for success in business and finance, including financial analysis, accounting, stock market investing, and project management. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Connect Power BI to databases, Excel, and cloud sources Model data with relationships and DAX measures Build interactive reports and dashboards Share Power BI reports across the organization Duration: Estimated duration: 120 hours of content, designed to be completed in 12-24 weeks at a comfortable pace. No prior experience is required. This course starts from the absolute basics and gradually builds up complexity. A computer with internet access is all you need to get started. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into business and finance Freelancers wanting to add new services to their portfolio Self-learners passionate about business and finance and wanting structured guidance Pricing: The course content is free to access. A verified certificate is available for a fee. Completing this resource and building related skills can prepare you for roles such as Financial Analyst, Business Analyst, Product Manager, Accountant. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 5-10 LPA Mid-level / 2-5 years: Rs 12-25 LPA Senior / 5+ years: Rs 28-55 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include banks, consulting firms, startups, Big 4 accounting firms. India's financial services sector is undergoing massive transformation with the rise of fintech, UPI, and digital banking. Financial literacy and business skills are valued across all industries, not just finance. Product managers, for instance, earn Rs 15-40 LPA and are one of the fastest-growing roles in Indian tech. Understanding business fundamentals gives you an edge regardless of your primary domain. Microsoft is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Microsoft Learn · Data Visualization
Microsoft Power BI - Free Learning Path is a comprehensive beginner-level resource offered by Microsoft Learn, focused on building practical skills in data science and analytics. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a structured online course with a carefully designed curriculum. Each module builds on the previous one, creating a logical progression from fundamentals to advanced topics. The course typically includes video lectures, reading materials, hands-on exercises, quizzes, and sometimes peer-reviewed assignments. This structured approach ensures you don't miss any critical concepts and build a solid foundation. This resource covers topics essential for success in data science and analytics, including Python, SQL, Pandas, NumPy, data visualization, statistics, and machine learning basics. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Connect Power BI to databases, Excel, and cloud sources Model data with relationships and DAX measures Build interactive reports and dashboards Share Power BI reports across the organization Duration: Estimated duration: 15 hours of content, designed to be completed in 2-3 weeks at a comfortable pace. No prior experience is required. This course starts from the absolute basics and gradually builds up complexity. A computer with internet access is all you need to get started. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into data science and analytics Freelancers wanting to add new services to their portfolio Self-learners passionate about data science and analytics and wanting structured guidance Pricing: This resource is completely free with no hidden charges. Completing this resource and building related skills can prepare you for roles such as Data Analyst, Business Analyst, Data Scientist, Analytics Engineer. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 4-8 LPA Mid-level / 2-5 years: Rs 10-22 LPA Senior / 5+ years: Rs 25-50 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include TCS, Infosys, Flipkart, Amazon, Swiggy, Zomato, PhonePe. The data science industry in India is projected to grow at 27% CAGR through 2028. Companies across all sectors — from banking (HDFC, ICICI) to e-commerce (Flipkart, Amazon) to healthcare (Practo, PharmEasy) — are building data teams. India currently has a shortage of 200,000+ data professionals, making this one of the best fields to enter right now. Cities like Bangalore, Hyderabad, Pune, and Gurgaon have the highest concentration of data science jobs. Microsoft Learn is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Microsoft Learn · Microsoft Azure
Microsoft Azure Fundamentals (AZ-900) is a comprehensive beginner-level resource offered by Microsoft Learn, focused on building practical skills in cloud computing and DevOps. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a structured online course with a carefully designed curriculum. Each module builds on the previous one, creating a logical progression from fundamentals to advanced topics. The course typically includes video lectures, reading materials, hands-on exercises, quizzes, and sometimes peer-reviewed assignments. This structured approach ensures you don't miss any critical concepts and build a solid foundation. This resource covers topics essential for success in cloud computing and DevOps, including AWS/Azure/GCP, Docker, Kubernetes, Terraform, CI/CD, and Linux administration. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Master core Azure services: VMs, Storage, App Service, SQL Database Deploy and manage workloads on Azure Implement Azure Active Directory and security controls Prepare for Microsoft Azure certifications Duration: Estimated duration: 10 hours of content, designed to be completed in 1-2 weeks at a comfortable pace. No prior experience is required. This course starts from the absolute basics and gradually builds up complexity. A computer with internet access is all you need to get started. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into cloud computing and DevOps Freelancers wanting to add new services to their portfolio Self-learners passionate about cloud computing and DevOps and wanting structured guidance Pricing: This resource is completely free with no hidden charges. Completing this resource and building related skills can prepare you for roles such as DevOps Engineer, Cloud Engineer, SRE, Platform Engineer. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 6-12 LPA Mid-level / 2-5 years: Rs 14-28 LPA Senior / 5+ years: Rs 30-60 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include Amazon, Microsoft, Flipkart, Ola, Jio, Infosys. Cloud computing adoption in India is growing at 30% annually, with AWS, Azure, and GCP leading the market. The DevOps engineer role is consistently ranked among the top 3 highest-paying IT jobs in India. The shift to microservices, containers, and cloud-native architectures means every tech company needs DevOps expertise. India alone has 100,000+ unfilled cloud computing positions, making this a seller's market for skilled professionals. Microsoft Learn is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Microsoft Learn · Deep Learning
Microsoft AI Learning Hub is a comprehensive beginner-level resource offered by Microsoft Learn, focused on building practical skills in artificial intelligence and machine learning. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a structured online course with a carefully designed curriculum. Each module builds on the previous one, creating a logical progression from fundamentals to advanced topics. The course typically includes video lectures, reading materials, hands-on exercises, quizzes, and sometimes peer-reviewed assignments. This structured approach ensures you don't miss any critical concepts and build a solid foundation. This resource covers topics essential for success in artificial intelligence and machine learning, including machine learning algorithms, deep learning, NLP, computer vision, and model deployment. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Understand the core concepts and theoretical foundations Apply your knowledge through hands-on exercises and small projects Build the practical skills employers actually screen for Develop the problem-solving approach used by working professionals Duration: Estimated duration: 20 hours of content, designed to be completed in 2-4 weeks at a comfortable pace. No prior experience is required. This course starts from the absolute basics and gradually builds up complexity. A computer with internet access is all you need to get started. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into artificial intelligence and machine learning Freelancers wanting to add new services to their portfolio Self-learners passionate about artificial intelligence and machine learning and wanting structured guidance Pricing: This resource is completely free with no hidden charges. Completing this resource and building related skills can prepare you for roles such as ML Engineer, AI Engineer, Data Scientist, Research Scientist. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 8-15 LPA Mid-level / 2-5 years: Rs 18-35 LPA Senior / 5+ years: Rs 40-80 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include Google, Microsoft, OpenAI, Indian AI startups, research labs. India is the second-largest AI talent pool globally, and the demand far exceeds supply. The Indian AI market is expected to reach $17 billion by 2027. Every major Indian tech company — from Infosys to Reliance to Jio — is investing heavily in AI capabilities. The emergence of generative AI has created entirely new job categories that didn't exist two years ago. ML engineers with LLM experience are commanding Rs 30-60 LPA even at early career stages. Microsoft Learn is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Microsoft (via FutureLearn) · Microsoft Azure
Introduction to DevOps - Microsoft (FutureLearn) is a comprehensive beginner-level resource offered by Microsoft, focused on building practical skills in cloud computing and DevOps. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a structured online course with a carefully designed curriculum. Each module builds on the previous one, creating a logical progression from fundamentals to advanced topics. The course typically includes video lectures, reading materials, hands-on exercises, quizzes, and sometimes peer-reviewed assignments. This structured approach ensures you don't miss any critical concepts and build a solid foundation. This resource covers topics essential for success in cloud computing and DevOps, including AWS/Azure/GCP, Docker, Kubernetes, Terraform, CI/CD, and Linux administration. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Master CI/CD pipelines, Infrastructure as Code, and observability Use Docker, Kubernetes, and Terraform together Automate testing, building, and deployment Bridge dev and ops teams effectively Duration: Estimated duration: 6 hours of content, designed to be completed in 1-2 weeks at a comfortable pace. No prior experience is required. This course starts from the absolute basics and gradually builds up complexity. A computer with internet access is all you need to get started. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into cloud computing and DevOps Freelancers wanting to add new services to their portfolio Self-learners passionate about cloud computing and DevOps and wanting structured guidance Pricing: This resource is completely free with no hidden charges. Completing this resource and building related skills can prepare you for roles such as DevOps Engineer, Cloud Engineer, SRE, Platform Engineer. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 6-12 LPA Mid-level / 2-5 years: Rs 14-28 LPA Senior / 5+ years: Rs 30-60 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include Amazon, Microsoft, Flipkart, Ola, Jio, Infosys. Cloud computing adoption in India is growing at 30% annually, with AWS, Azure, and GCP leading the market. The DevOps engineer role is consistently ranked among the top 3 highest-paying IT jobs in India. The shift to microservices, containers, and cloud-native architectures means every tech company needs DevOps expertise. India alone has 100,000+ unfilled cloud computing positions, making this a seller's market for skilled professionals. Microsoft is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Microsoft · Data Visualization
This course portrays how Copilot can be leveraged in conjunction with Power BI to streamline process and enhance work outputs. It provides a general overview as well as detailed use case demonstrations for Power BI practitioners who want to augment their skills with Generative AI.
Microsoft · Deep Learning
Explore the diverse and powerful world of core generative AI. This course provides a comprehensive survey of the fundamental models that power modern AI, including Generative Adversarial Networks (GANs), autoregressive models, and diffusion models. You will build a strong foundation, understanding the unique architectures and training strategies for each, and compare essential frameworks like PyTorch and TensorFlow. The course then moves into hands-on implementation. You will learn to generate sequential data, such as time-series forecasts, using advanced autoregressive models in Azure AI Foundry. Next, you will master the art of high-fidelity image generation, using diffusion models to create and edit stunning visuals with techniques like inpainting and outpainting. Finally, you will learn to accelerate your development workflow by using Azure ML Designer, a visual, low-code environment for rapid prototyping. You will practice designing, building, evaluating, and preparing sophisticated model pipelines for real-world deployment. This course equips you not just with knowledge of different models, but with the practical skills to build and prototype them effectively on Azure.
Microsoft · React & Next.js
This course provides a comprehensive guide to using GitHub Copilot within the Visual Studio Code environment, focusing on practical and advanced applications. The course covers building a simple Pomodoro timer, including setting up the Next.js environment, designing the timer interface, and implementing core functionality, as well as improving the timer by refactoring for efficiency, adding tests, and exploring case studies. The course also focuses on practical coding applications, such as code translation and debugging, through hands-on activities. Throughout the course, you will engage in practical projects, quizzes, and hands-on activities to master the use of GitHub Copilot, making it ideal for developers looking to enhance their coding efficiency and explore the full potential of AI-assisted development. Required Course Materials: A Copilot license is required to complete this course. If you don’t have a Microsoft 365 Personal or Family license, you can start a free 30-day trial using the link provided in the course.
Microsoft · Software Engineering
This course equips you with the essential skills to take generative AI models from development to production. You will learn to implement robust MLOps practices on Azure, including automated CI/CD pipelines, version control, and full lifecycle management for your models. Simultaneously, you will dive into the critical principles of Responsible AI, using Microsoft’s framework to build fair, transparent, and ethical models that you can deploy with confidence.
Microsoft · Big Data & Data Engineering
In this course, you will learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build your foundational knowledge of cloud data services within Microsoft Azure. You will identify and describe core data concepts such as relational, non-relational, big data, and analytics, and explore how this technology is implemented with Microsoft Azure. You will explore the roles, tasks, and responsibilities in the world of data. This is the first course in a program of five courses to help prepare you to take the Exam DP-900: Microsoft Azure Data Fundamentals. so that you can demonstrate that you have a foundational knowledge of the core database concepts in a cloud environment. This course is ideal for IT professionals who want to learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure with a view to taking up roles as Data Engineers and Database Administrators. It is also suitable for working database professionals looking for additional skills or credentials to showcase expertise in a cloud environment and IT professionals looking to specialize in the specific area of Azure data. To be successful in this course, you need to have basic computer literacy and proficiency in the English language. Successful Azure Data Fundamentals students start with some basic awareness of computing and Internet concepts, and an interest in extracting insights from data. It is an advantage to have experience using a web browser, familiarity with basic data-related concepts, such as working with tables of data in a spreadsheet, and visualizing data using charts.
Microsoft · Microsoft Azure
In this course, you will learn how to work with the Azure command line and web portal to create, manage, and control cloud-based resources. You will look at all three approaches to deploying cloud resources and how to make an informed decision about which one to leverage for your services. You'll also quickly look at the service models supported by Azure which can help you determine the services you should start with when planning out an Azure deployment. You will learn how to install the Azure CLI locally and use it to manage Azure resources. You will also use Azure PowerShell interactively for one-off tasks and write scripts to automate repeated tasks. You'll learn about the major factors that influence the cost of running in the cloud. Along the way, you'll get hands-on experience with some of the tools you can use to estimate the costs of running your workloads on Azure to help ensure that you stay within budget and use only the services that you need. Azure Resource Manager has a number of features that you can use to organize resources, enforce standards, and protect critical Azure resources from accidental deletion. In this module, you'll take a tour through these features, and examine how you can use them to your advantage. You'll identify incorrectly assigned resources in Azure. You'll also assess whether resources can be moved, and validate a resource move operation. Then you'll move and verify resources between Azure resource groups. This course will help you prepare for the Microsoft Certified: Azure Developer Associate certification. In this course, you will take a practice exam that covers key skills measured in the exam. This is the fifth course in a program of 8 courses to help prepare you to take the exam. This course is part of a Specialization intended for developers who want to demonstrate their expertise in all phases of cloud development from requirements, definition, and design; to development, deployment, and maintenance; to performance ...
Microsoft · Data Analysis
Transform raw data into valuable insights using R's powerful tidyverse tools. This beginner-friendly course introduces you to essential data cleaning and manipulation techniques, making complex data tasks approachable and practical. Learn how to clean messy data, handle missing values, and prepare datasets for analysis using Microsoft's development environment and AI assistance. Through hands-on practice, you'll master fundamental data cleaning skills while building confidence in: Organizing and structuring data effectively Handling common data issues Working with different data formats Using AI tools to enhance your workflow Creating reproducible data cleaning processes Each concept is taught step-by-step with extensive examples and guided practice, ensuring you build a strong foundation in data manipulation skills.
Microsoft · Natural Language Processing
This course focuses on the design and implementation of intelligent troubleshooting agents. You will learn to create AI-powered agents that can diagnose and resolve issues autonomously. The course covers natural language processing, decision-making algorithms, and best practices in AI agent development. By the end of this course, you will be able to: 1. Define, describe, and design the architecture of an intelligent troubleshooting agent. 2. Implement natural language processing techniques for user interaction. 3. Develop decision-making algorithms for problem diagnosis and resolution. 4. Optimize and evaluate the performance of AI-based troubleshooting agents. To be successful in this course, you should have intermediate programming knowledge of Python, plus experience with AI & ML infrastructure and core algorithms and techniques, including approaches using pretrained large-language models (LLMs). Familiarity with statistics is also recommended.
Microsoft · Python Programming
Azure Machine Learning is a cloud platform for training, deploying, managing, and monitoring machine learning models. In this course, you will learn how to use the Azure Machine Learning Python SDK to create and manage enterprise-ready ML solutions. This is the third course in a five-course program that prepares you to take the DP-100: Designing and Implementing a Data Science Solution on Azurecertification exam. The certification exam is an opportunity to prove knowledge and expertise operate machine learning solutions at a cloud-scale using Azure Machine Learning. This specialization teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Each course teaches you the concepts and skills that are measured by the exam. This Specialization is intended for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. It teaches data scientists how to create end-to-end solutions in Microsoft Azure. Students will learn how to manage Azure resources for machine learning; run experiments and train models; deploy and operationalize machine learning solutions, and implement responsible machine learning. They will also learn to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning.
Microsoft · C# & .NET
This course introduces the fundamentals of ASP.NET Core, its architecture, and development environment setup. Learners will understand how ASP.NET Core differs from the .NET Framework, gain hands-on experience creating their first ASP.NET Core application, explore Blazor for building interactive web UIs, and integrate client-side technologies to enhance user experience. By the end of this course, you will be able to: Explain the fundamentals of ASP.NET Core framework and its role in web development. Set up and configure a development environment for ASP.NET Core applications. Create a simple ASP.NET Core web application and implement basic routing. Develop interactive web UIs using Blazor components and various render modes. Integrate client-side technologies like JavaScript and CSS with ASP.NET Core applications.
Microsoft · Big Data & Data Engineering
In this course, you will learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build your foundational knowledge of cloud data services within Microsoft Azure. You will explore the processing options available for building data analytics solutions in Azure. You will explore Azure Synapse Analytics, Azure Databricks, and Azure HDInsight. This is the fourth course in a program of five courses to help prepare you to take the Exam DP-900: Microsoft Azure Data Fundamentals. so that you can demonstrate that you have a foundational knowledge of the core database concepts in a cloud environment. This course is ideal for IT professionals who want to learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure with a view to taking up roles as Data Engineers and Database Administrators. It is also suitable for working database professionals looking for additional skills or credentials to showcase expertise in a cloud environment and IT professionals looking to specialize in the specific area of Azure data. To be successful in this course, you need to have basic computer literacy and proficiency in the English language. Successful Azure Data Fundamentals students start with some basic awareness of computing and Internet concepts, and an interest in extracting insights from data. It is an advantage to have experience using a web browser, familiarity with basic data-related concepts, such as working with tables of data in a spreadsheet, and visualizing data using charts.
Microsoft · Generative AI & LLMs
In this course, it is necessary to have access to Microsoft 365 with Copilot enabled, although no prior experience with Copilot is needed. You'll explore how to use Copilot Pro and Microsoft 365 Copilot in Excel to work with data more efficiently. You'll learn to transform raw data into meaningful insights and eye-catching visualizations, all with the help of AI. You'll cover advanced techniques for manipulating data, generating insights, creating visualizations, and summarizing information using Copilot in Excel. By the end of the course, you'll be able to: • Manipulate and analyze datasets using Copilot in Excel. • Generate valuable insights from a provided dataset. • Create effective data visualizations using natural language prompts with Copilot in Excel. • Synthesize and summarize information into concise, actionable formats. With these skills, you'll be ready to tackle data challenges confidently and enhance your productivity using Excel and AI-powered tools. Required Course Materials: A Copilot license is required to complete this course. If you don’t have a Microsoft 365 Personal or Family license, you can start a free 30-day trial using the link provided in the course.
Microsoft · Big Data & Data Engineering
This advanced course teaches machine learning and AI techniques for big data systems. Learners will build end-to-end ML pipelines with PySpark ML, implement supervised and unsupervised models, and apply NLP techniques at scale. The course also explores deep learning, distributed training, and integrating Generative AI into big data workflows. By the end of this course, you will be able to: Implement ML pipelines using PySpark ML Build supervised, unsupervised, and recommendation models Apply NLP and text analytics to large datasets -Integrate Generative AI and LLMs with big data systems Tools & Software: PySpark ML, PyTorch, TensorFlow, Azure Machine Learning, Azure OpenAI Service Skills: Machine learning, NLP, Deep learning, Generative AI, Model evaluation
Microsoft · Machine Learning
Machine learning is the foundation for predictive modeling and artificial intelligence. If you want to learn about both the underlying concepts and how to get into building models with the most common machine learning tools this path is for you. In this course, you will learn the core principles of machine learning and how to use common tools and frameworks to train, evaluate, and use machine learning models. This course is designed to prepare you for roles that include planning and creating a suitable working environment for data science workloads on Azure. You will learn how to run data experiments and train predictive models. In addition, you will manage, optimize, and deploy machine learning models into production. From the most basic classical machine learning models, to exploratory data analysis and customizing architectures, you’ll be guided by easy -to-digest conceptual content and interactive Jupyter notebooks. If you already have some idea what machine learning is about or you have a strong mathematical background this course is perfect for you. These modules teach some machine learning concepts, but move fast so they can get to the power of using tools like scikit-learn, TensorFlow, and PyTorch. This learning path is also the best one for you if you're looking for just enough familiarity to understand machine learning examples for products like Azure ML or Azure Databricks. It's also a good place to start if you plan to move beyond classic machine learning and get an education in deep learning and neural networks, which we only introduce here. This program consists of 5 courses to help prepare you to take the Exam DP-100: Designing and Implementing a Data Science Solution on Azure. The certification exam is an opportunity to prove knowledge and expertise operate machine learning solutions at cloud scale using Azure Machine Learning. This specialization teaches you to leverage your existing knowledge of Python and machine learning to manage data ingest...
Microsoft · Big Data & Data Engineering
Microsoft Azure provides a comprehensive suite of security tools and services to help you safeguard your organization's data and applications. Secure access with Azure Active Directory is the right course if you are interested in an IT security career and becoming an Azure security engineer. In this course, you will learn about Azure Active Directory (Azure AD) and the various roles in Azure AD. You will learn to create and manage users and groups in Azure AD and manage administrative units. The content covers adding, updating, deleting, and restoring users and managing licenses. You will also delve into Azure AD Domain Services. You will learn how to authenticate and authorize users and apps with Azure AD and password management. You will learn about multifactor and passwordless authentication. Additionally, you will learn how to implement pass-through authentication and federation with Azure AD. You will gain insight into deploying and configuring Azure AD Connect to create a hybrid identity solution for your organization. This is the first course in a series of seven courses that will prepare you to succeed in the AZ-500 exam.