Skip to content
🎄 Special Offer! 🎅🎁 Flat 40% OFF on all courses!
All Courses
Programming Courses
Python Certification Training Course
Trending
Python Django Certification Training Course
Node.js Certification Training Course
Java Certification Training Course
Best Seller
Spring Framework Certification Training Course
Spring Boot Certification Training Course
Trending
Hibernate Certification Training Course
Microsoft .NET Framework Certification Training Course
Data Analytics Certification Training Course
Trending
PHP MYSQL with MVC Certification Training Course
Advanced Java Certification Training
Go Language Certification Training
Flutter Certification Training
Get your free demo class
Call Us
Master Program
Full Stack Certification Training Course
Trending
DevOps Master Program Certification Training Course
New
Cloud Masters Program Certification Training Course
Popular
Data Science Master Program Certification Training Course
Popular
Software Testing Master Program Certification Training Course
Get your free demo class
Call Us
Cloud Computing
AWS Solution Architect Associate Certification Training
Trending
AWS Certified DevOps Engineer Professional Training
Popular
AWS Development Certification Training Course
New
Microsoft Azure Certification Training Course (AZ-104 & AZ-304)
Microsoft Azure DevOps Certification Training Course (AZ-400)
Microservices Certification Training Course
Salesforce Developer Certification Training Course
Salesforce Administrator Certification Training Course
Linux Certification Training Course
Get your free demo class
Call Us
DevOps
DevOps Certification Training Course
Trending
Kubernetes Certification Training Course
Docker Certification Training Course
Ansible Certification Training Course
Chef Certification Training Course
GIT Certification Training Course
DevSecOps Certification Training Course in Bangalore
Get your free demo class
Get now
Data science
DataScience with Python Certification Training Course
Best Seller
Machine Learning Certification Training Course
Deep Learning Certification Training Course
(AI) Artificial Intelligence Certification Training Course
Trending
Get your free demo class
Call Us
Big Data
Big Data Hadoop Certification Training Course
Trending
Apache Spark and Scala Certification Training Course
Apache Kafka Certification Training Course
Best Seller
Get Your Free Demo Class
Call Us
Software Testing
Selenium Certification Training Course
Trending
Selenium with Python Certification Training Course
New
Selenium with C# Certification Training Course
Manual Testing Certification Training Course
Get your free demo class
Call Us
Robotic Process Automation
RPA using UiPath Certification Training Course
Trending
RPA using Automation Anywhere Certification Training Course
RPA using Blue Prism Certification Training Course
Get your free demo class
Call Us
Frontend Development
Angular Certification Training Course
Trending
React JS Certification Training Course
Best Seller
Web Development Certification Training Course
MERN Stack Certification Training Course
Get your free demo class
Call Us
Databases
MySQL Certification Training Course
Oracle Certification Training Course
MongoDB Certification Training Course
Trending
Get your free demo class
Call Us
Mobile Development
Android Certification Training Course
Trending
Get your free demo class
Call Us
Placement Records
Placement Records
Interview Preperation
About
FAQs
Blog
Gallery
X
Contact Us
eMexo Technologies
MLOps Certification Training
Curriculum
11 Sections
55 Lessons
10 Weeks
Expand all sections
Collapse all sections
Introduction to MLOps
5
1.1
What is MLOps?
1.2
Importance of MLOps in modern AI/ML lifecycle
1.3
Traditional ML workflow vs MLOps workflow
1.4
MLOps principles: CI/CD, automation, reproducibility, scalability
1.5
Case studies of MLOps in industry
ML Lifecycle & Version Control
5
2.1
ML development lifecycle: data → model → deployment → monitoring
2.2
Data versioning with DVC / Git LFS
2.3
Model versioning with MLflow / Weights & Biases
2.4
Experient tracking & collaboration
2.5
Hands-on: Track datasets & mML experiments with MLflow; store and retrieve multiple model versions
CI/CD for Machine Learning
5
3.1
Overview of CI/CD in MLOps
3.2
Automating ML pipelines using Jenkins / GitHub Actions / GitLab CI
3.3
Integrating code linting, testing & packaging
3.4
Automating training workflows
3.5
Hands-on: Set up a CI/CD pipeline to train & test an ML model automatically
Containerization & Orchestration
6
4.1
Introduction to Docker for ML applications
4.2
Building Docker images for ML models
4.3
Introduction to Kubernetes (K8s)
4.4
Deploying ML workloads on Kubernetes
4.5
Scaling and monitoring ML services in production
4.6
Hands-on: Containerize an ML model using Docker; deploy on Kubernetes cluster
Model Deployment Strategies
6
5.1
Deployment options: batch, real-time, streaming
5.2
Serving ML models with Flask / FastAPI
5.3
Model serving with TensorFlow Serving / TorchServe
5.4
REST API & gRPC endpoints for ML models
5.5
Canary deployments, blue-green deployment strategies
5.6
Hands-on: Deploy ML model as REST API on Azure Web App / AWS Sagemaker / GCP AI Platform
ML Pipelines & Workflow Automation
5
6.1
Introduction to pipelines (Kubeflow, TFX, Airflow, Prefect)
6.2
Data preprocessing pipelines
6.3
Model training & evaluation pipelines
6.4
Automated retraining pipelines
6.5
Hands-on: Create an end-to-end ML pipeline using Kubeflow or Airflow
Monitoring & Logging in Production
5
7.1
Importance of monitoring ML systems
7.2
Concept drift, data drift & model performance monitoring
7.3
Logging with ELK stack / Prometheus & Grafana
7.4
Alerting & automated retraining triggers
7.5
Hands-on: Implement monitoring dashboard for deployed ML model
Cloud & MLOps Tools
3
8.1
AWS Sagemaker, Azure ML, GCP Vertex AI overview
8.2
MLOps with cloud-native tools
8.3
Cost optimization strategies for ML workflows
Security, Compliance & Governance
3
9.1
Data security in ML pipelines
9.2
Model explainability & fairness
9.3
Governance, audit trails & compliance (GDPR, HIPAA, etc.)
Capstone Project
6
10.1
End-to-End MLOps Pipeline covering
10.2
Data collection & preprocessing
10.3
Model training & versioning
10.4
CI/CD pipeline for ML model
10.5
Containerization & deployment on cloud/K8s
10.6
Monitoring & retraining setup
Tools Covered
6
11.1
Versioning & Tracking: Git, DVC, MLflow, Weights & Biases
11.2
CI/CD: Jenkins, GitHub Actions, GitLab CI
11.3
Containers & Orchestration: Docker, Kubernetes, Helm
11.4
Model Serving: Flask, FastAPI, TensorFlow Serving, TorchServe
11.5
Pipelines: Airflow, Kubeflow, TFX, Prefect
11.6
Cloud Platforms: AWS Sagemaker, Azure ML, GCP Vertex AI Monitoring: Prometheus, Grafana, ELK Stack
This content is protected, please
login
and
enroll
in the course to view this content!
Modal title
Main Content