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Machine Learning Operations (MLOps) Training Course In Australia

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Enhance your expertise with the Machine Learning Operations (MLOps) Online Training Course in Australia by Multisoft Virtual Academy. This course equips professionals with the skills to streamline machine learning workflows and improve collaboration between data scientists and operations teams, promoting efficient deployment and scaling of ML models.

Duration

24Hrs.

Experience & Certified

Trainers

Type of Batch

WeekEnd/WeekDay

Program Formate

Online

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Instructor-led Training Live Online Classes

Suitable batches for you

	28 Dec 2024	24	06:00 PM - 09:00 PM	Sat, Sun
	29 Dec 2024	24	06:00 PM - 09:00 PM	Sat, Sun

Course Price At

$ 450

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Instructor-led Training Live Online Classes

	28 Dec 2024	24	06:00 PM - 09:00 PM	Sat, Sun
	29 Dec 2024	24	06:00 PM - 09:00 PM	Sat, Sun

Course Price At

$ 450

Enroll Now

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Online Self Learning Courses are designed for self-directed training, allowing participants to begin at their convenience with structured training and review exercises to reinforce learning. You’ll learn through videos, PPTs and complete assignments, projects and other activities designed to enhance learning outcomes, all at times that are most convenient to you.

Course Price At

$ 450

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Machine Learning Operations (MLOps) Online Training Course In Australia Course Syllabus

Curriculum Designed by Experts

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MLOps training teaches the skills needed to efficiently manage machine learning operations, focusing on automating and streamlining the machine learning lifecycle. It covers deploying, monitoring, and maintaining ML models, ensuring they perform optimally and integrate seamlessly with existing IT environments. The training also emphasizes collaboration and continuous improvement in ML projects.

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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Machine Learning Operations (MLOps) Online Training Course In Australia Description

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.

The target audience for MLOps training includes:

Data Scientists
Machine Learning Engineers
DevOps Engineers
IT Professionals
Software Developers
Data Engineers

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.

Machine Learning Operations (MLOps) Online Training Course In Australia Certification

Multisoft Virtual Academy provides a globally recognized training certificate to the participants, after successful completion of a training program. The training certificates are recognized and accepted across the world.

Multisoft Virtual Academy's training certificate comes with lifetime validity.

Aspirants can directly enroll for the desired course from the Book Now Button in the course page. You can also connect on Whatsapp at +91 8130666206 to talk with a training advisor. Multisoft Virtual Academy also offers customized training programs on a wide range of domains and skills.

All training programs offered by Multisoft Virtual Academy are delivered by certified industry experts, who have years of experience in the relevant domains. Multisoft Global Subject Matter Experts impart knowledge on a wide variety of training courses through one –on-one and corporate training sessions.

Multisoft Virtual Academy training certification can help participants stand out in the competitive job market. Since the training certificates are internationally accepted, participants can showcase their skills and knowledge to employers across the world.

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Machine Learning Operations (MLOps) Online Course In Australia Corporate Training Certification

Interactive Virtual Training

Global Subject Matter Experts
Step-by –Step Learning Approach
Instant Doubt Clearing

Lifetime Access

Lifetime E-learning Access
Recorded Training Session Videos
Free Access to Practice Tests

24x7 Assistance

Help Desk Support
Doubt Resolution in Real-time
After Training Support

Hands on Experience

Project Based Learning
Learning based on real-life examples
Assignments and Practice Tests

Globally Recognized Certificate

Multisoft Training Certificate
Globally Recognized and Accepted
Lifetime Validity

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Machine Learning Operations (MLOps) Online Training Course In Australia FAQ's

Multisoft Virtual Academy offer a certification upon completion of the course, which can be beneficial for professional recognition and career advancement.

Yes, Multisoft Virtual Academy offer online MLOps courses that you can attend from anywhere, providing flexibility to fit your schedule.

MLOps training enhances your ability to deploy, monitor, and maintain machine learning models efficiently, increases collaboration among teams, and improves your skills in automation and best practices in machine learning operations.

Participants will learn about the lifecycle of machine learning models including development, deployment, and maintenance. The course covers model versioning, monitoring, automation with CI/CD pipelines, and the use of tools to enhance collaboration and efficiency.

To contact Multisoft Virtual Academy you can mail us on enquiry@multisoftvirtualacademy.com or can call for course enquiry on this number +91 8130666206