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This MLOps training program offers a thorough guide on how to deploy, monitor, and manage machine learning models. Participants will acquire a deep understanding of MLOps concepts, SDLC methodologies, and model management tasks, and they will learn how to effectively use version control systems, package ML models, and create ML applications with cutting-edge tools. Practical sessions will enhance their learning experience, delving into areas like CI/CD implementation, Docker, Kubernetes, and model monitoring.
The course will also cover the utilization of cloud platforms such as Amazon SageMaker and Azure Machine Learning Studio for ML development and deployment. Moreover, participants will tackle post-deployment issues such as model integrity and adversarial attacks, gaining valuable insights into model evaluation and risk management strategies.
The MLOps Course is a comprehensive program that covers a wide range of topics, including the significance of deploying, monitoring, and managing machine learning models in real-world scenarios, as well as MLOps concepts, SDLC methodologies, and model management practices.
The aim of MLOps is to close the gap between data scientists and IT teams, ensuring speedy, reliable, and scalable deployment of machine learning models.
This course is well-suited for programmers, developers, data analysts, statisticians, data scientists, and software engineers.
To excel in MLOps, one must know programming languages like Python, understand ML algorithms, be familiar with deployment tools like Docker and Kubernetes, and be knowledgeable about cloud platforms.
The system requirements for this MLOps Course includes:
Practicals for this course will be implemented using various tools and detailed step-by-step installation guidesfor these tools are available on the LMS. In case you come across any doubt, the 24*7 support teams will promptly assist you.
There are simple steps to enroll in this MLOps certification course:
Edureka provides lifetime access to the course content. You can come back any time if you want to brush up your knowledge.
If you missed out on joining our current batch, then you can connect with our experts to get you enrolled in the next batch.
We take each feedback seriously. So after completing every class, our Edureka support team will contact you for your valuable feedback on the course.
Yes, we are providing corporate training for this MLOps course.
Edureka offers various AI-related courses such as Artificial Intelligence Certification Course , ChatGpt Course , Machine Learning Certification Training .
Edureka provides free learning resources to help you understand the technology better, such as Blog and AI Community . You can explore some trending blogs like AI for Startups, Generative AI vs. Predictive AI , Generative AI Models.
Here are a few simple and effective steps to become a MLOps Engineer:
Learn ML concepts, algorithms, and frameworks.
Understand DevOps concepts.
Get hands-on experience in MLOps tools like MLflow, Kubernetes, Docker, etc.
To acquire your practical skills work with industry experts and do the practice as well.
Keep continuously learning new tools, techniques, and best practices in MLOps and machine learning.
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