Program Highlights
The Microsoft Azure Machine Learning Operations Training Course offered by InfosecTrain provides a thorough learning on the effective implementation of machine learning operations within the Azure cloud environment. This extensive course encompasses all aspects of MLOps, including establishing Azure ML workspaces and deploying and maintaining machine learning models.
16 Hours of Instructor-led Training 
Certificate of Participation 
Learn with a Practical Approach 
Highly Interactive and Dynamic Sessions 
Learn from Industry Experts 
Career Guidance and Mentorship 
Post Training Support 
Access to Recorded Sessions
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- 1 on 1 training
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The Azure Machine Learning Operations (MLOps) training course at InfosecTrain equips participants with skills to manage and optimize the machine learning lifecycle on Azure. This course covers the fundamentals of Azure MLOps, including setting up an Azure ML workspace and integrating Azure DevOps with GitHub. Participants will learn to create, run, and manage ML experiments and pipelines, employ version control and utilize continuous integration techniques. They will also deploy ML models via Azure Kubernetes Service and use tools like Application Insights for management. The course wraps up with best practices to ensure participants can apply these skills effectively in real-world scenarios.
Module 1:
Introduction to Azure ML Ops
Module 2:
Setting up the Azure ML Ops Environment
Module 3:
Creating and Running Azure ML Experiments
Module 4:
Creating and Managing Azure ML Pipelines
Module 5:
Version Control and Collaboration with Azure ML Ops
Module 6:
Model Deployment with Azure ML Ops
Module 7:
Monitoring and Maintaining Azure ML Deployments
Module 8:
Wrap-up and Next Steps
- Data Scientists
- DevOps Engineers
- ML Engineers
- Cloud Engineers
- IT Professionals
- Software Developers
- Technical Project Managers
- AI Architects
- Quality Assurance Engineers
- Technical Leads
- Basic understanding of cloud computing, especially Microsoft Azure services.
- Familiarity with Azure fundamentals, including portal navigation and cloud resource management.
- Experience with Python programming for machine learning scripting.
- Basic understanding of machine learning principles and experience in constructing foundational models.
- Understanding of DevOps principles, focusing on CI/CD processes.
- Experience with version control systems such as Git, essential for teamwork and collaborative software development.
You will be able to:
- Learn how MLOps in Azure helps improve the entire machine-learning process.
- Set up an Azure ML workspace and connect it with Azure DevOps and GitHub to streamline code updates and deployment.
- Run Azure ML experiments to refine your machine learning models continually.
- Develop and manage Azure ML Pipelines to automate and enhance machine learning operations.
- Use version control for machine learning projects to track changes and collaborate more effectively.
- Work together efficiently using Azure ML Ops tools to boost productivity and reduce mistakes in machine learning development.
- Deploy and manage machine learning models on Azure Kubernetes Service (AKS) effectively within the Azure ML framework.
- Use Application Insights to monitor your machine learning applications and learn how to scale and update models in production.
- Address common problems in Azure ML deployments to reduce downtime and maintain model quality.
- Implement MLOps best practices in Azure and plan how to integrate these methods into your company’s processes.
How We Help You Succeed
Vision
Goal
Skill-Building
Mentoring
Direction
Support
Success
Career Transformation
will grow exponentially over the next decade.
reducing deployment cycles
of organizations plan to recruit certified Azure MLOps professionals.
of organizations are investing in training their existing staff in Azure Machine Learning Operations.
Technology
Healthcare
Retail
Government
Manufacturing
Finance
Words Have Power
The training was awesome. Helped me clear my concepts and also reduced my preparation time to 1/3rd. Thank you, trainer, for all your dedication to bring your gladiators to pace.
I loved the training. Coming for more soon. The trainer is easily reachable and helpful.. I loved the staggered payment option given.
I must say the admin team is excellent and punctual. The trainers are actually the nerve of the team and know how to engage with the students across all the topics.
Thoroughly enjoyed the course and the continuous support from the entire team..
It was a good experience. Looking forward to career growth with Infosectrain. Thank you
Really interesting courses are delivered by really knowledgeable instructors. Worth the fees
Success Speaks Volumes
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Frequently Asked Questions
What is MLOps training?
MLOps training equips individuals with the skills to apply best practices and technologies for automating and optimizing the lifecycle of machine learning models in production. This includes model building, testing, deployment, and monitoring.
Who should enroll in the MLOps course?
- Data Scientists
- DevOps Engineers
- ML Engineers
- Cloud Engineers
- IT Professionals
- Software Developers
- Technical Project Managers
- AI Architects
- Quality Assurance Engineers
- Technical Leads
What is Machine Learning?
Machine Learning is a branch of artificial intelligence that involves training algorithms to recognize patterns and make data-based decisions, without being explicitly programmed.
What is MLOps?
MLOps, or Machine Learning Operations, is the practice of collaboration and communication between data scientists and operations professionals to help manage the production ML (or deep learning) lifecycle.
How is MLOps different from DevOps?
While DevOps focuses on the continuous integration and delivery of software, MLOps specifically targets the unique needs of machine learning projects, such as managing data models, versioning, and experiment tracking.
What are the prerequisites for the MLOps training?
- Basic understanding of cloud computing, especially Microsoft Azure services.
- Familiarity with Azure fundamentals, including portal navigation and cloud resource management.
- Experience with Python programming for machine learning scripting.
- Basic understanding of machine learning principles and experience in constructing foundational models.
- Understanding of DevOps principles, focusing on CI/CD processes.
- Experience with version control systems such as Git, essential for teamwork and collaborative software development.
How long is the MLOps training?
The duration of the MLOPs training is 16 hours.
Will I receive a certification upon completion of the MLOps course?
Yes, you will receive a certificate upon successful completion.
What are the benefits of MLOps training?
- Improved skills in managing and deploying machine learning models.
- Enhanced collaboration abilities between teams.
- Better job prospects and career advancement opportunities.
Can I take the MLOps course online?
Yes, you can take the MLOPs course online.
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