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Machine Learning Simplified

From Ideation to Deployment with Azure Machine Learning

Microsoft Ignite 2019 | Machine Learning Simplified: From Ideation to Deployment with Azure Machine Learning | Erez Barak, Anita Klopfenstein

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Microsoft Ignite 2019 | Machine Learning Simplified: From Ideation to Deployment with Azure Machine Learning | Erez Barak, Anita Klopfenstein

Artificial intelligence is right here, right now—and making AI real for businesses is our goal. Azure Machine Learning offers powerful tools for all levels of data science, including a powerful, simple drag and drop authoring environment with no-code needed. You can go from ideation to deployment in a matter of clicks and visually design your machine learning models with ease. Whether you are new to machine learning, a data scientist or a developer, you can leverage this platform to accelerate your data science journey.

This course is no longer available. Find a similar course by searching these:
anita klopfenstein machine learning simplified azure machine learning erez barak drag and drop authoring environment data science

What's inside

Syllabus

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Introduces the machine learning process from ideation to deployment, making it accessible to learners with no-code experience
Suitable for learners of all skill levels in data science, including beginners with no prior machine learning knowledge
Leverages the Azure Machine Learning platform, a powerful and user-friendly environment for designing machine learning models
Provides hands-on experience through drag-and-drop authoring and visual design of machine learning models

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Activities

Coming soon We're preparing activities for Machine Learning Simplified: From Ideation to Deployment with Azure Machine Learning. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Machine Learning Simplified: From Ideation to Deployment with Azure Machine Learning will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists take raw data and transform it into actionable insights to help businesses grow and make better decisions. This course may help aspiring Data Scientists by providing an overview of machine learning and how to apply it to real-world problems using Azure Machine Learning.
See salaries and explore the career path for Data Scientist
Machine Learning Engineer
Machine Learning Engineers build, deploy, and maintain machine learning models that solve real-world problems. This course may help aspiring Machine Learning Engineers by providing a hands-on introduction to machine learning and Azure Machine Learning.
See salaries and explore the career path for Machine Learning Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course may help aspiring Software Engineers by providing an overview of machine learning and how to apply it to build intelligent software systems.
See salaries and explore the career path for Software Engineer
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns that help businesses make better decisions. This course may help aspiring Data Analysts by providing an overview of machine learning and how to apply it to analyze data.
See salaries and explore the career path for Data Analyst
Business Analyst
Business Analysts help businesses understand their operations and processes and identify opportunities for improvement. This course may help aspiring Business Analysts by providing an overview of machine learning and how to apply it to analyze business data.
See salaries and explore the career path for Business Analyst
Project Manager
Project Managers plan, execute, and close projects. This course may help aspiring Project Managers by providing an overview of machine learning and how to apply it to manage projects.
See salaries and explore the career path for Project Manager
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve complex business problems. This course may help aspiring Operations Research Analysts by providing an overview of machine learning and how to apply it to solve business problems.
See salaries and explore the career path for Operations Research Analyst
Product Manager
Product Managers develop and manage products and services. This course may help aspiring Product Managers by providing an overview of machine learning and how to apply it to develop and manage products.
See salaries and explore the career path for Product Manager
Statistician
Statisticians collect, analyze, and interpret data to help businesses make better decisions. This course may help aspiring Statisticians by providing an overview of machine learning and how to apply it to analyze data.
See salaries and explore the career path for Statistician
Financial Analyst
Financial Analysts analyze financial data to help businesses make investment decisions. This course may help aspiring Financial Analysts by providing an overview of machine learning and how to apply it to analyze financial data.
See salaries and explore the career path for Financial Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze financial data and make investment decisions. This course may help aspiring Quantitative Analysts by providing an overview of machine learning and how to apply it to analyze financial data.
See salaries and explore the career path for Quantitative Analyst
Risk Analyst
Risk Analysts identify and assess risks to help businesses make informed decisions. This course may help aspiring Risk Analysts by providing an overview of machine learning and how to apply it to assess risks.
See salaries and explore the career path for Risk Analyst
Actuary
Actuaries use mathematical and statistical techniques to assess risks and design insurance and pension plans. This course may help aspiring Actuaries by providing an overview of machine learning and how to apply it to assess risks and design insurance and pension plans.
See salaries and explore the career path for Actuary
Data Engineer
Data Engineers design, build, and maintain data pipelines. This course may help aspiring Data Engineers by providing an overview of machine learning and how to apply it to design and build data pipelines.
See salaries and explore the career path for Data Engineer
Machine Learning Researcher
Machine Learning Researchers develop new machine learning algorithms and techniques. This course may help aspiring Machine Learning Researchers by providing an overview of the state-of-the-art in machine learning and how to conduct machine learning research.
See salaries and explore the career path for Machine Learning Researcher

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Time
55 hours
Level
Introductory
Via
Pluralsight
Language
English
This course belongs to a collection called Microsoft Ignite 2019: Breakouts. It's comprised of 69 courses:
  1. Machine Learning Simplified: From Ideation to Deployment with Azure Machine Learning (viewing)
  2. Knowledge Mining: AI-driven Content Understanding with Cognitive Search on Azure
  3. AI Powered Web Search with Bing Search APIs, and More
  4. Manage Your End-to-end Machine Learning Lifecycle with MLOps
  5. Getting Your Data Ready to Train Computer Vision Models Using Azure Machine Learning
  6. A Deep-dive into Conversational AI using Azure Bot Service and Cognitive Services
  7. Enterprise AI Scenarios for Speech, Technical Edition
  8. Understanding AI Enabled Search for Your Apps: Azure Search Technical Edition
  9. Building Industrial Autonomous Systems with Reinforcement Learning
  10. Increase Your .NET Productivity with Visual Studio and Visual Studio for Mac
  11. Cloud Native Applications with .NET Core and Azure Kubernetes Service
  12. Create Amazing Web Apps with ASP.NET Core
  13. Debugging Tips and Tricks in Visual Studio 2019
  14. Visual Studio Online: A Look at the Future of Developer Productivity and Collaboration
  15. Linux based Web App Development Made Easy on App Service
  16. APIs and Digital Transformation: Growing Your Business with Connected Ecosystems
  17. .NET Platform Overview and Roadmap
  18. Java on Azure: Building Spring Boot Microservices
  19. What’s New in Security for Azure SQL
  20. Raising the Bar Again for Azure SQL Database with Centrally Managed Encryption
  21. Understanding the Latest Updates in Azure Cosmos DB API for Mongo DB and Best Practices
  22. Data Modelling and Partitioning in Azure Cosmos DB: What Every Relational Database User Needs to Know
  23. Building Event Driven Apps with Azure Cosmos DB and Azure Functions
  24. A Developer's Guide to Azure Cosmos DB, from Onboarding to Going Live in Production
  25. Migrate or Build Internet-scale Applications Using MySQL
  26. Mission Critical Performance with SQL Server 2019
  27. SQL Server 2019 Big Data Clusters: Architecture, Deployment, and Security
  28. SQL Server 2019 on Containers and Kubernetes
  29. Best, Better, Hyperscale: The Last Database You Will Ever Need in the Cloud
  30. Gaining Business Insights with Open Source Analytics on Azure HDInsight: Patterns and Best Practices
  31. Migrating Your Mission-Critical Data Warehouse to Azure Synapse Analytics
  32. Deep Dive with Data Migration Tools and Azure Database Migration Service
  33. PaaSport to Paradise: Lifting and Shifting with Azure SQL Database + SSIS in Azure Data Factory
  34. Learn Why SAP Customers with Leading Brands and Large Mission Critical Landscapes Are Migrating Their SAP to Azure
  35. Driving Retail and Manufacturing Industry Transformation with SAP on Azure
  36. Lessons Learned Migrating SAP Applications to Azure: Customers and Partners
  37. Make the Most of Azure to Reduce Your Cloud Spend
  38. Oracle on Azure Overview
  39. What's New in Azure Networking
  40. Get Your Organization Ready for Your Azure Journey
  41. Introducing Azure Arc
  42. End to End Security for IoT
  43. Best Practices and Lessons Learned from Securely Operating Microsoft Azure Stack
  44. PowerShell Unplugged with Jeffrey Snover and Jason Helmick
  45. Learn How to Run Network-attached Storage Workflows in Azure
  46. Use GPU VMs to Power Remote Graphics and Visualization in the Cloud
  47. Modernize Your Retail Stores or Branch Offices with Azure Stack HCI
  48. Jumpstart Your Azure Stack HCI Deployment
  49. Building High-value Integrated Data Center Solutions for Microsoft Azure Stack
  50. Customizing Images Made Easy for Windows & Linux on Azure with Azure Image Builder Service and Shared Image Gallery
  51. Global Transit Network Architectures with Azure Virtual WAN
  52. Windows Admin Center: Unlock Azure Hybrid Value
  53. Delivering Services Privately in Your VNet with Azure Private Link
  54. Virtual Machine Manager 2019 and Data Protection Manager 2019: Customer Success Stories and What’s Next
  55. Azure Automation for Managing Servers across Your Environment
  56. PowerShell 7
  57. Automate and Manage Your Windows Server Environment Using Azure Management Services
  58. Architecting SAP Landscapes with Demanding Performance Requirements on Azure
  59. Seamless Connectivity to Azure with Windows Server and Hybrid Networking
  60. Files Are Critical to Your Business: Modernize Your File Services with Windows Server 2019 and Azure
  61. Bringing File Services into the 2020s: Migrate SMB and NFS File Shares to the Cloud with Azure Files and Sync
  62. Plan for Z-day 2020: Windows Server 2008 End of Support is Coming!
  63. Use Serverless Technologies to Manage Your IT Resources
  64. What’s Next for Software-defined Storage and Networking for Windows Server
  65. Leverage the Cloud to Strengthen Your On-premises Active Directory Security
  66. Optimize Price-performance and Lower TCO for Your Workloads with the Next-gen Azure Disks
  67. Creating Impact Today with Microsoft Quantum
  68. Microsoft Quantum: Partners in Action
  69. Driving Growth and Transformation with Microsoft IoT
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Introduces the machine learning process from ideation to deployment, making it accessible to learners with no-code experience
Suitable for learners of all skill levels in data science, including beginners with no prior machine learning knowledge
Leverages the Azure Machine Learning platform, a powerful and user-friendly environment for designing machine learning models
Provides hands-on experience through drag-and-drop authoring and visual design of machine learning models
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