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MLOps Certification Training Course

MLOps Certification Training Course

Name: MLOps Certification Training Course
Item: MLOps Certification Training Course
Rating: 5
Author: Eric Arnaud

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Edureka's MLOps Certification training online will help you prepare for ML for Ops Architect, MLOps Engineer, MLOps Lead, etc. It covers tools, techniques, and best practices for managing the entire ML lifecycle, from data ingestion to model deployment and monitoring. You will learn how to apply DevOps principles to machine learning, enabling the smooth deployment and maintenance of ML models in production.

7k+ satisfied learners Read Reviews

Why should you take MLOps Certification Training Course?

Global MLOps market is expected to reach $75.42 billion by 2033 from $2.08 billion in 2024 at a CAGR of 43.2% - Market.us

Large enterprises dominate the MLOps market, possessing a significant 71% share in the year 2023 - Market.us

The average salary for MLOps Engineer is $1,76,248 per year in the United States with a $38,892 cash bonus per year - Glassdoor

Instructor-led MLOps Certification Training Course live online classes

May 31 ^st

Sat & Sun (5 Weeks) Weekend Batch

Sold Out Timings - 11:00 AM to 02:00 PM (EDT)

Jun 20 ^th

Fri & Sat (5.5 Weeks) Weekend Batch

Filling Fast Timings - 09:30 PM to 10:30 PM (EDT) ORIENTATION CLASS

Jul 19 ^th

Sat & Sun (5.5 Weeks) Weekend Batch

Timings - 11:00 AM to 12:00 PM (EDT) ORIENTATION CLASS

Course Price at

296 349

Can’t find a batch you were looking for?

Curriculum

MLOps Essentials

Topics:

Introduction to MLOps
MLOps vs. DevOps
SDLC Basics
Waterfall vs AGILE vs DevOps vs MLOps
MLOps Phases
Versioning
Testing
Automation
Reproductibility
Deployment
Monitoring
MLOPs Architecture
ML Pipeline
MLOps Tools
MLOPs Case Study

Hands-on:

MLOps Case Study

Skills You will Learn

Understanding MLOps Concepts
Proficiency in SDLC Methodologies

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Version Control System

Topics:

Git Essentials
Configuring Git
Branching
Git Workflow
Repo
Git Commands
GitHub Action

Hands-on:

Git Common Commands
Branching and Merging

Skills You will Learn

Tracking and managing changes to code
Source Code Management
Tracking and Saving Changes in Files

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Packaging ML Models

Topics:

Model Packaging
Experimentation
Model Fitting
Challenges in Working inside the Jupyter Notebook
Create Config Module
Data Handling Module
Data Preprocessing Data Preprocessing
Pipelines
Training and Prediction
Requirements.txt file
Testing Virtual Environments
Pytest
Model Packaging and Testing

Hands-on:

ML Model Packaging and Testing

Skills You will Learn

Model Packaging Techniques
Data Preprocessing and Handling s
Testing and Validation of ML models

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Build MLApps using New Age Tools

Topics:

API Essentials
Streamlit Fundamentals
Working with Flask
REST API
FAST API
Building ML Model with Streamlit
Creating ML Model with Flask
ML Model Deployment with FAST API

Hands-on:

Developing ML models using Streamlit
Building ML models using Flask
Deploying ML models using FAST API

Skills You will Learn

ML Application Development
ML Pipelines with FAST API

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CI/CD for ML Models

Topics:

Introduction to CI/CD
CI/CD Challenges
CI/CD Implementation in ML
Popular DevOps Tools
AWS CodeCommit
AWS CodePipeline
AWS CodeBuild
AWS CodeDeploy
Azure Boards
Azure Repos
Azure Pipeline
Azure Test Plans
Azure Artifacts

Hands-on:

Building CI/CD Pipelines

Skills You will Learn

Implementation of CI/CD Pipelines for ML

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Machine Learning Model Management

Topics:

What is Model Management?
Activities in Model Management
Data Versioning
Code Versioning
Experiment Tracking
Model Cataloging
Model Monitoring
Overview of Model Management tools
Working with MLFlow

Hands-on:

Working with MLFlow

Skills You will Learn

Data Management
Code Versioning
Experiment Tracking

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Docker and Kubernetes for ML Deployment

Topics:

Containerization
Docker
Docker Architecture
Docker for Machine Learning
Docker Desktop Installation
Working with Docker
Running Docker Container
Dockerfile
Pushing Docker Image to DockerHub
Dockerize the ML Model
Container Orchestration
Kubernetes Core Concepts
Pod
Deployment
Replica
Service
Volumes (PVC)
Monitoring
Liveness and Readiness Probes
Labels and Selectors

Hands-on:

Docker CLI Commands
Writing a Dockerfile Deployments
DaemonSets
Deploying Services

Skills You will Learn

Continuous Deployment
Writing a Dockerfile to Create an Image
Installing Docker Compose
Configuring Local Registry
Container Orchestration
Application Deployment

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Monitoring and Debugging of ML System

Topics:

Model Monitoring Importance
Tools for Model Monitoring
Understanding ML Model Monitoring
Challenges in Monitoring ML Models
Exploring Model Drift Phenomenon
Operational Level Monitoring Insights
Introduction to Prometheus Monitoring System
WhyLabs Setup Process
Exploring WhyLogs Features: Drift Detection, Input/Output Monitoring, Bias Detection
WhyLogs Usage: Constraints and Drift Reports

Hands-on:

ML Model Monitoring
Monitoring using WhyLogs

Skills You will Learn

Model Monitoring and Debugging

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Kubeflow for Building ML Pipelines

Topics:

Kubeflow Introduction
Features
Kubeflow Fairing
Kubeflow Pipelines
Working with Kubeflow

Hands-on:

Building ML Pipeline with Kubeflow

Skills You will Learn

Building end-to-end ML pipelines with Kubeflow

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MLOps on Cloud

Topics:

Getting Started with Amazon Sagemaker
Amazon SageMaker Notebooks Overview
Configuration of Notebook Instance
Creating, Training, and Deploying ML Models with Sagemaker
Setting up Endpoints and Endpoint Configurations
Executing Inference from Deployed Models
Exploring SageMaker Studio & Domain Features
Introduction to SageMaker Projects
Understanding Repositories in SageMaker
Utilizing Pipelines and Graphs in SageMaker
Conducting Experiments with SageMaker
Managing Model Groups in SageMaker
Configuring Endpoints in SageMaker
Introduction to Azure Machine Learning Studio
Exploring Azure MLOps
Understanding Azure ML Components
Integration of Azure MLOps with DevOps
Setting up Fully Automated End-to-End CI/CD ML Pipelines

Hands-on:

Building an end-to-end MLOps pipeline using AWS SageMaker

Skills You will Learn

Using Amazon SageMaker for ML development and deployment
Management of ML Models and Experiments using Azure Machine Learning

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ML Model Post Deployment Challenges (Self-paced)

Topics:

Ensuring Model Integrity
Counteracting Adversarial Attacks
Guarding Against Data Poisoning
Preventing Distributed Denial of Service (DDOS)
Safeguarding Data Privacy
Strategies for Mitigating Model Attack Risks
Implementing A/B Testing Methodologies
Outlook on the Future of MLOps

Hands-on:

Implementing A/B Testing Methodologies

Skills You will Learn

Implementation of A/B testing methodologies for model evaluation
Strategies for Ensuring model Integrity and Security

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Course Details

About your MLOps Course

This course provides a comprehensive introduction to Machine Learning Operations (MLOps), focusing on the reliable and efficient deployment and management of ML models in production. It covers key stages like model development, deployment, monitoring, and optimization. Students will gain practical experience with leading MLOps tools and frameworks, equipping them to build scalable and production-ready ML workflows.

Who should take up this Course?

This course is well-suited for programmers, developers, data analysts, statisticians, data scientists, and software engineers.

What are the prerequisites for this certification Course?

To excel in MLOps, you need Python skills, ML algorithm knowledge, experience with Docker, Kubernetes, and cloud platforms. A laptop with at least 8GB RAM, Intel i3+ processor, and stable internet is also required.

How will I execute the practicals in this course?

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.

How do I enroll for this training?

There are simple steps to enroll in this MLOps certification course:

Check the Course Details
Create an Account
Click Enroll now
Select your Batch and Timing
Complete your Payment
Get a confirmation mail
Start learning
Missed the current batch? Connect with our experts to join the next one.

Can I access the course materials after completing the training?

Edureka provides lifetime access to the course content. You can come back any time if you want to brush up your knowledge.

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Testimonial Reviews

Eric ArnaudPhD candidate in computer engineering speciality applied cryptography at Korea University of Technology and Education

I would like to recommend any one who wants to be a Data Scientist just one place: Edureka. Explanat ... Read More

Gagan Maheshwari

Thanks a lot for your Android course. Right from the point of the start of the demo class, until the ... Read More

Tejinder SinghPGDCA, MSc(IT), MCA, M-tech(IT), Phd(CS)*, Lecturer, Baba Farid College, Punjab

There is a plethora of online training material available for Android; the reason I chose Edureka is ... Read More

Amit VijHRSSC HRIS Senior Advisor at DLA Piper

I am not a big fan of online courses and also opted for class room based training sessions in past. ... Read More

Zakir KhanSenior Associate, Syntel, Thane, Maharashtra, India

The unique combination of Online Classes with 24*7 On-Demand Support and class recordings/ppt/docs e ... Read More

Praveen KonkisaBI Architect & Hadoop Specialist at Teradata

I have taken Informatica, Hadoop, R-programming, Spark and Scala and several other training's from p ... Read More

Video Reviews

Vinayak shares his Edureka learning experience and how our Big Data training helped him achieve his dream career path.

Our learner Balasubramaniam shares his Edureka learning experience and how our training helped him stay updated with evolving technologies.

Sriram speaks about his learning experience with Edureka and how our Hadoop training helped him execute his Big Data project efficiently.

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FAQs

What is MLOps?

MLOps, or Machine Learning Operations, is a set of practices designed to streamline the development, deployment, and maintenance of machine learning models, much like DevOps but tailored specifically for ML workflows.

Will I get placement assistance after completing this MLOps Training?

No, we do not provide placement assistance. The focus is on providing in-depth knowledge and hands-on skills to help you advance your career independently.

Who are the instructors for MLOps Course?

All the instructors at edureka are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by edureka for providing an awesome learning experience to the participants.

What if I have more queries after completion of MLOps Course?

Just give us a CALL at +91 98702 76459/1844 230 6365 (US Tollfree Number) OR email at sales@edureka.co.

What if I miss a class ?

You can easily catch up on missed lectures through recorded sessions in your LMS or by joining a live session in another batch.

What skills do I need to learn for MLOps?‎

You need strong programming skills, proficiency in infrastructure as code, an understanding of cloud services, and knowledge of machine learning concepts and frameworks to learn MLOps.

Why MLOps is Important?

Bridges the gap between data science and software engineering for faster and more reliable ML deployments.

Improves model performance and ensures higher reliability in production.

Automates and streamlines the ML lifecycle, enhancing efficiency and scalability.

What will be the mode and duration of this training?

We only offer live online training on weekends for a course duration of 5.5 weeks.

Does MLOps require coding?

Yes, MLOps generally requires coding knowledge because developers need it for MLOps to deploy models in production environments.

What is the cost of MLOps course in India?

The cost of the MLOps certification course in India is INR 21,999

Is MLOps better than DevOps?

MLOps focuses on automating machine learning tasks such as model training, while DevOps focuses on traditional software development tasks such as code deployment and builds.

What language is best for MLOps?

Python is the best language for MLOps

What is the significance of MLOps in the machine learning lifecycle?

The importance of MLOps in machine learning is to ensure faster deployment and easier troubleshooting.

What is the role of MLOps engineer?

They deploy, manage, and optimize machine learning models in production environments to ensure smooth integration and efficient operations.

What is the salary of MLOps analyst?

According to Glassdoor, the average salary for MLOps Engineer/Analyst is ₹11,64,260 per year in India.

Does MLOps have a future?

MLOps is a powerful and essential approach shaping the future of Machine Learning, and it's one of the most in-demand and rewarding skills to learn in 2024. With AI and ML being adopted across industries, MLOps roles are growing rapidly, offering strong career growth and competitive salaries from both a technical and business perspective.

What are the differences between DevOps and MLOps?

Both MLOps and DevOps are different. MLOps is based on Machine Learning While DevOps is based on development. In DevOps tools like Jenkins, GitLab CI, and Travis CI are used. In MLOps tools like MLflow, Weights & Biases are used.

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Structure your learning and get a certificate to prove it.

MLOps Certification Training Course

Why should you take MLOps Certification Training Course?

Instructor-led MLOps Certification Training Course live online classes

Financing Options

Curriculum

MLOps Essentials

Version Control System

Packaging ML Models

Build MLApps using New Age Tools

CI/CD for ML Models

Machine Learning Model Management

Docker and Kubernetes for ML Deployment

Monitoring and Debugging of ML System

Kubeflow for Building ML Pipelines

MLOps on Cloud

ML Model Post Deployment Challenges (Self-paced)

Course Details

About your MLOps Course

Who should take up this Course?

What are the prerequisites for this certification Course?

How will I execute the practicals in this course?

How do I enroll for this training?

Can I access the course materials after completing the training?

Testimonial Reviews

Video Reviews

FAQs

What is MLOps?

Will I get placement assistance after completing this MLOps Training?

Who are the instructors for MLOps Course?

What if I have more queries after completion of MLOps Course?

What if I miss a class ?

What skills do I need to learn for MLOps?‎

Why MLOps is Important?

What will be the mode and duration of this training?

Does MLOps require coding?

What is the cost of MLOps course in India?

Is MLOps better than DevOps?

What language is best for MLOps?

What is the significance of MLOps in the machine learning lifecycle?

What is the role of MLOps engineer?

What is the salary of MLOps analyst?

Does MLOps have a future?

What are the differences between DevOps and MLOps?

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