Instructor-Led Training Parameters

Course Highlights

  • Instructor-led Online Training
  • Project Based Learning
  • Certified & Experienced Trainers
  • Course Completion Certificate
  • Lifetime e-Learning Access
  • 24x7 After Training Support

MLOps Training Online Course Overview

Unlock the full potential of machine learning with MLOps training by Multisoft Systems. Gain expertise in continuous integration, delivery, and automation. Elevate your career with our expert-led sessions that ensure you stay at the forefront of technology trends in machine learning.

MLOps, or Machine Learning Operations, is an essential discipline for professionals involved in machine learning, aiming to streamline the lifecycle of ML models from development to deployment and maintenance. Multisoft Systems' MLOps training program is meticulously designed to equip learners with the critical skills needed to manage and automate ML models efficiently. This course covers various aspects of MLOps, including model development, version control, testing, deployment, and monitoring. Participants will learn how to integrate machine learning models into production environments seamlessly, ensuring they perform optimally in real-world scenarios. The training also emphasizes the importance of collaboration between data scientists and operations teams to foster a more productive and agile environment.

Key components of the program include hands-on exercises and real-world case studies, which provide participants with practical experience in applying MLOps tools and techniques. Learners will delve into the use of popular platforms and technologies such as Docker, Kubernetes, and CI/CD pipelines, which are pivotal in the efficient management of ML projects. Upon completion of the training, participants will not only understand the foundational elements of MLOps but also be able to implement best practices and methodologies that enhance the scalability and reliability of machine learning systems. This training is ideal for data scientists, ML engineers, and IT professionals eager to advance their knowledge and careers in this dynamic field.

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MLOps Training Online Course curriculum

Curriculum Designed by Experts

Unlock the full potential of machine learning with MLOps training by Multisoft Systems. Gain expertise in continuous integration, delivery, and automation. Elevate your career with our expert-led sessions that ensure you stay at the forefront of technology trends in machine learning.

MLOps, or Machine Learning Operations, is an essential discipline for professionals involved in machine learning, aiming to streamline the lifecycle of ML models from development to deployment and maintenance. Multisoft Systems' MLOps training program is meticulously designed to equip learners with the critical skills needed to manage and automate ML models efficiently. This course covers various aspects of MLOps, including model development, version control, testing, deployment, and monitoring. Participants will learn how to integrate machine learning models into production environments seamlessly, ensuring they perform optimally in real-world scenarios. The training also emphasizes the importance of collaboration between data scientists and operations teams to foster a more productive and agile environment.

Key components of the program include hands-on exercises and real-world case studies, which provide participants with practical experience in applying MLOps tools and techniques. Learners will delve into the use of popular platforms and technologies such as Docker, Kubernetes, and CI/CD pipelines, which are pivotal in the efficient management of ML projects. Upon completion of the training, participants will not only understand the foundational elements of MLOps but also be able to implement best practices and methodologies that enhance the scalability and reliability of machine learning systems. This training is ideal for data scientists, ML engineers, and IT professionals eager to advance their knowledge and careers in this dynamic field.

Here are the key objectives of the MLOps training:

  • Gain a thorough understanding of the complete machine learning lifecycle, including development, deployment, monitoring, and scaling.
  • Learn to utilize essential MLOps tools and technologies such as Docker, Kubernetes, and continuous integration/continuous deployment (CI/CD) pipelines effectively.
  • Enhance collaboration between data scientists, developers, and operational teams to streamline the deployment and maintenance of ML models.
  • Acquire skills to automate various stages of the ML workflow, improving efficiency and reducing human error.
  • Learn techniques to monitor and maintain deployed models to ensure they remain accurate and performant over time.

Course Prerequisite

  • Familiarity with machine learning concepts and algorithms.
  • Proficiency in programming languages such as Python, which is commonly used in machine learning.
  • Knowledge of handling data sets, data preprocessing, and data storage techniques.

Course Target Audience

The target audience for MLOps training includes:

  • Data Scientists
  • Machine Learning Engineers
  • DevOps Engineers
  • IT Professionals
  • Software Developers
  • Data Engineers
  • Analytics Managers

Course Content

  • Overview of ML Ops principles and importance
  • Challenges in deploying and managing machine learning models
  • Introduction to the course structure and objectives

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  • Basics of version control
  • Introduction to Git and its importance in ML Ops
  • Hands-on exercises on Git commands for managing machine learning models, datasets, and code

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  • Introduction to Docker and containerization
  • Dockerfile creation and container management
  • Docker for packaging machine learning models

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  • Overview of Kubernetes and container orchestration
  • Deploying and scaling machine learning models with Kubernetes
  • Hands-on exercises on Kubernetes deployment

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  • Introduction to CI/CD and its importance in ML Ops
  • Setting up CI/CD pipelines for machine learning models
  • Automation of testing, building, and deployment processes

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  • Importance of monitoring and logging in ML Ops
  • Implementing monitoring solutions for tracking model performance and health
  • Hands-on exercises on monitoring tools

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  • Understanding model governance and compliance
  • Techniques for ensuring fairness, transparency, and accountability in machine learning models
  • Case studies on model governance

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  • Techniques for optimizing scalability and performance of machine learning models
  • Hands-on exercises on performance optimization

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  • Introduction to Infrastructure as Code (IaC)
  • Provisioning and managing infrastructure using Terraform
  • Hands-on exercises on Terraform for ML Ops

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  • Importance of security in ML Ops
  • Security best practices for machine learning models
  • Techniques for protecting against threats and vulnerabilities

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  • Presentation of real-world case studies and best practices from industry experts
  • Discussion on challenges and solutions in implementing ML Ops in various organizations
  • Q&A session

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MLOps Training (MCQ) Assessment

This assessment tests understanding of course content through MCQ and short answers, analytical thinking, problem-solving abilities, and effective communication of ideas. Some Multisoft Assessment Features :

  • User-friendly interface for easy navigation
  • Secure login and authentication measures to protect data
  • Automated scoring and grading to save time
  • Time limits and countdown timers to manage duration.
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MLOps Corporate Training

Employee training and development programs are essential to the success of businesses worldwide. With our best-in-class corporate trainings you can enhance employee productivity and increase efficiency of your organization. Created by global subject matter experts, we offer highest quality content that are tailored to match your company’s learning goals and budget.


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Customized Training

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Mentors

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360º Learning Solution

Be it schedule, duration or course material, you can entirely customize the trainings depending on the learning requirements

Learning Assessment

Be it schedule, duration or course material, you can entirely customize the trainings depending on the learning requirements

Certification Training Achievements: Recognizing Professional Expertise

Multisoft Systems is the “one-top learning platform” for everyone. Get trained with certified industry experts and receive a globally-recognized training certificate. Some Multisoft Training Certificate Features :

  • Globally recognized certificate
  • Course ID & Course Name
  • Certificate with Date of Issuance
  • Name and Digital Signature of the Awardee
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MLOps Training Online FAQ's

  • MLOps, or Machine Learning Operations, is a set of practices that aims to streamline and automate the machine learning lifecycle, from development to deployment and maintenance.

  • MLOps training is ideal for data scientists, machine learning engineers, DevOps engineers, IT professionals, and anyone involved in the development and deployment of machine learning models.

  • Attendees should have basic knowledge of machine learning, proficiency in a programming language (preferably Python), and some understanding of data management and software development practices.

  • You will learn about the end-to-end machine learning lifecycle, including model development, deployment, monitoring, and scaling, as well as the use of tools and technologies like Kubernetes and CI/CD pipelines.

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