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We're here to help you find itMLOps on Azure: From Data Science to Deployment certification leverages Microsoft Azure tools to integrate machine learning (ML) outcomes into business processes. It is all about learning to streamline Machine Learning Life Cycle using Azure's Machine Learning Operations (MLOps) capabilities. Industries use this to ensure reproducibility, auditing, and automation of their ML models in production, leading to a consistent and efficient creation of business value. It's comprised of concepts like developing ML models with Azure ML service, controlling ML model versions, validating ML models, creating retraining pipelines, deploying ML models into production, and monitoring ML models. It essentially gives shape to operationalizing machine learning by managing end-to-end life cycle of ML models.
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♱ Excluding VAT/GST
Classroom Training price is on request
You can request classroom training in any city on any date by Requesting More Information
- Solid understanding of data science and Machine Learning concepts
- Familiarity with Python or another programming language
- Basic knowledge of Azure services
- Experience with utilizing cloud platforms for data management
- Understanding of DevOps and its methodologies
- Skills in developing and deploying ML models.
The MLOps on Azure: From Data Science to Deployment certification training focuses on operationalizing Machine Learning models efficiently. Course instruction includes creating experiment pipelines, tracking metrics, managing models, deploying to production, and applying responsible AI principles. This training helps data scientists and engineers leverage Azure as a platform for model lifecycle management, enabling them to manage and automate Machine Learning model workflows from development to deployment.
Learning MLOps on Azure enhances understanding of Machine Learning workflows, automating tasks and scaling up processes. It equips learners with knowledge of creating repeatable and reliable ML pipelines. The course also offers hands-on experience to deploy, manage, monitor, and version ML models, improving data science skills and employability in the tech industry.
- Data Scientists and Engineers looking to operationalize machine learning models
- IT professionals aiming to streamline and manage ML operations on Azure platform
- ML practitioners seeking a thorough understanding of concepts like deployment, versioning, and monitoring of ML models
- Individuals with interest in Azure cloud platform services and MLOps methodologies.
- Learn from certified instructors experienced in MLOps on Azure.
- Boost your career opportunities in the data science field by adding MLOps on Azure to your skillset.
- Take advantage of customized training programs tailored to your learning pace and needs.
- Attend this course anywhere either through instructor-led online training or destination training for versatile learning methods.
- Enjoy affordable pricing options without compromising on the quality of education.
- Flexible dates are available to accommodate different schedules and timeframes.
- Benefit from choosing a top and accredited training institute recognized in the industry for high standards.
- Explore a wide range of courses offered by Koenig Solutions to enhance your professional growth.
After completing the MLOps on Azure certification training, an individual will gain the skills in implementing Machine Learning solutions, managing the end-to-end ML lifecycle and automating the ML workflows on Azure. They will be proficient in operationalizing and managing machine learning models by using Azure Databricks, Azure ML services and ML pipelines. Furthermore, they will be able to use Azure DevOps for version control, testing, and deployment, conform to data privacy and security regulations, and manage the auditing, logging, and monitoring of ML solutions.
Major companies like Microsoft, IBM, Accenture, Cognizant, Capgemini, and Deloitte are among the top recruiters hiring MLOps on Azure certified professionals. These firms seek individuals who can efficiently manage machine learning lifecycle and deployment using Azure's comprehensive suite of tools and services.
The learning objectives of the MLOps on Azure: From Data Science to Deployment course are designed to impart the skills required to execute machine learning operations in Azure. These objectives include understanding the key principles and practices of MLOps, learning how to set up a MLOps environment in Azure, as well as understanding how to deploy, monitor, and manage machine learning models. The course would also focus on automating and streamlining the machine learning pipeline, optimize resources, conduct data science experiments, and ensure continuous integration, delivery, and training of the models. It further aims to train participants in using Azure services for releasing models more effectively.
- Data Scientists and Engineers looking to operationalize machine learning models
- IT professionals aiming to streamline and manage ML operations on Azure platform
- ML practitioners seeking a thorough understanding of concepts like deployment, versioning, and monitoring of ML models
- Individuals with interest in Azure cloud platform services and MLOps methodologies.
- Learn from certified instructors experienced in MLOps on Azure.
- Boost your career opportunities in the data science field by adding MLOps on Azure to your skillset.
- Take advantage of customized training programs tailored to your learning pace and needs.
- Attend this course anywhere either through instructor-led online training or destination training for versatile learning methods.
- Enjoy affordable pricing options without compromising on the quality of education.
- Flexible dates are available to accommodate different schedules and timeframes.
- Benefit from choosing a top and accredited training institute recognized in the industry for high standards.
- Explore a wide range of courses offered by Koenig Solutions to enhance your professional growth.
After completing the MLOps on Azure certification training, an individual will gain the skills in implementing Machine Learning solutions, managing the end-to-end ML lifecycle and automating the ML workflows on Azure. They will be proficient in operationalizing and managing machine learning models by using Azure Databricks, Azure ML services and ML pipelines. Furthermore, they will be able to use Azure DevOps for version control, testing, and deployment, conform to data privacy and security regulations, and manage the auditing, logging, and monitoring of ML solutions.
Major companies like Microsoft, IBM, Accenture, Cognizant, Capgemini, and Deloitte are among the top recruiters hiring MLOps on Azure certified professionals. These firms seek individuals who can efficiently manage machine learning lifecycle and deployment using Azure's comprehensive suite of tools and services.
The learning objectives of the MLOps on Azure: From Data Science to Deployment course are designed to impart the skills required to execute machine learning operations in Azure. These objectives include understanding the key principles and practices of MLOps, learning how to set up a MLOps environment in Azure, as well as understanding how to deploy, monitor, and manage machine learning models. The course would also focus on automating and streamlining the machine learning pipeline, optimize resources, conduct data science experiments, and ensure continuous integration, delivery, and training of the models. It further aims to train participants in using Azure services for releasing models more effectively.
