Introduction   Building production solutions that take full advantage of the Microsoft AI products and services is exhilarating, and the results are real. Learning how to do so in an efficient manner can be challenging since there are many technologies to learn which, in turn, must be integrated within existing operating environments to add value for a customer.   This article aims to provide learning resources and guidance for architecting and deploying end-to-end AI solutions. Whether you’re a developer who seeks to embed AI in your solutions, a DBA looking for AI data engineering skills, or a data scientist who wants to go deeper into the state-of-the-art AI services, this post is for you.   Learn the Technologies   The learning resources for technical roles are immense so we’ve limited our selection to the Microsoft offerings that can provide quick access to the learning paths for using Microsoft AI.   Microsoft Learn Microsoft Learn provides learning paths and materials to learn about Microsoft products and technology in short, easy to consume, modules. Whether you’re looking to hone your skills in preparation for one of the AI role certification exams or have a half hour and want to learn something new, Microsoft Learn is your destination to achieve your learning goals faster.   AI School and Labs As you begin to dive into AI, you have a couple of choices depending upon what your needs are.   If you’re looking for product information, learning materials and resources you need to start building intelligence into your solutions, go to the Microsoft’s AI School. All courses are free, self-paced, on-demand, and organized into learning paths. And, you can create your own learning path, with total customization for your own needs.   If you want to explore code for and play around with some of the latest breakthrough AI innovations by Microsoft, check out our AI Lab. The content is organized by stories, intelligent building blocks, and application samples.     Microsoft AI Platform and Microsoft Docs To learn about the full range of Microsoft products and services, you’ll want to visit – and bookmark – the Microsoft AI Platform site.  You will find information about our products and services as well as technology-agnostic AI methodologies, curated datasets and open source tools. For the active AI professional, it’ll be your go-to site to check on feature announcements and updates.   Of course, as with  all Microsoft products, docs.microsoft.com is the home for Microsoft documentation for end users, developers, and IT professionals. Docs hosts Quick Start's, tutorials, API reference, and code examples.   Get Certified on Data & AI   Certifications are an important part of a technical professional’s credentials. Microsoft offers role-based certifications that, upon successfully completing exams, shows you are keeping pace with today’s technical roles and requirements. The Data & AI track has four certifications and, to achieve them, you can use MS Lean's learning paths or take an instructor-led course from the Microsoft Learning Partners to prepare. Here are the key links for the certifications: Azure AI Engineer Azure Data Scientist Azure Data Engineer   Image 1: Azure Data & AI Certifications   Create End-to-End Solutions   Now that you went through the individual technologies, it is time to learn how to connect them into an End-to-End (E2E) solution to get your business challenges addressed with AI. This is the next level of AI learning and you need to learn how to integrate products and services, including (relevant links included):   Azure Machine Learning Conversational AI Cognitive Services Knowledge Mining Azure Machine Learning Pipelines Automated Machine Learning AI Compute Targets Model Management with MLOps Continuous Integration and Continuous Delivery (CI/CD) Azure Notebooks Open AI with ONNX IoT – AI on Edge Devices   As an example, check out the AML Pipeline below using the Azure ML service. All AI E2E solutions have a pipeline and, to make it production worthy, will also need a CI/CD process with MLOps to retrain the model, republish it, and track its performance as customer data and requirements evolve. Notice how the workflow that is created integrates the customer’s user experience, data stores, and compute targets. This is a reference architecture that is applicable to most industries including fintech, health, and retail. You may also want to check out other reference architectures for good solution building ideas.   Image 2: Example of an E2E AI Pipeline   These are the kinds of learnings that one can acquire either from years of experience working with the technologies or by taking a workshop, like the Microsoft Cloud Workshop or Microsoft Professional Program, described below.   Microsoft Cloud Workshop - MCW The Microsoft Cloud Workshop is a hands-on community development experience complete with trainer preparation materials and instructive videos on how to redeliver the content, if necessary. The community is hosted on GitHub and features a variety of workshops including one on Cognitive Services and Deep Learning.   Conclusion   Engineering E2E solutions using AI requires the ability to stitch together multiple technologies in your customer’s environment for maximum results. Start with learning, get certified, and then get building. We’ve assembled this table to help you keep track of this actively evolving AI landscape and resources.   When you want to… What to use Learn more about AI Microsoft Learn and AI School Find product information Microsoft AI Platform and Microsoft Docs Pitch about AI in minutes AI Demos Create E2E solutions Microsoft Cloud Workshop Get an AI certification Microsoft Learning Create AI for a good cause AI for Good Test AI AI Lab Use AI Microsoft AI Platform Table 1: Guide to Learning Resources depending on what you want   Check this blog series frequently: it is where we post our best practices and lessons learned from working with our top customers and partners as they advance on their AI journeys. That can only mean good outcomes for you and your customers!