MLOps Masterclass
Beginner
- 1 Section
- 2 Lessons
- 1 Quiz
- 0m Duration
Section1
2 Lessons
1 Quiz
ML Ops Masterclass overview
Master building and deploying production-ready ML and LLM systems
What you'll learn
- Master Python fundamentals, MLOps principles, and data management to build and deploy ML models in production environments.
- Utilize Amazon SageMaker / AWS, Azure, MLflow, and Hugging Face for end-to-end ML solutions, pipeline creation, and API development.
- Fine-tune and deploy Large Language Models (LLMs) and containerized models using the ONNX format with Hugging Face.
- Design a full MLOps pipeline with MLflow, managing projects, models, and tracking system features.
Skills you'll gain
MLOps (Machine Learning Operations)
Python Programming
AWS SageMaker
Microsoft Azure
Data Management
Data Pipelines
Big Data
DevOps
CI/CD
Containerization
Responsible AI
Machine Learning
Cloud Computing
Pandas
NumPy
Data Analysis
Data Manipulation
Exploratory Data Analysis
Application Deployment
GitHub
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from Jingle AI Academy**
5 Star
0%
4 Star
100%
3 Star
0%
2 Star
0%
1 Star
0%
Want to submit a review? Login and enrolled
Reviews
-
Dec 9, 2025 @ 11:54 amsample comment
This course includes
✔ Master end-to-end ML pipelines — data ingestion → training → deployment
✔ Work with top MLOps tools — Docker, Kubernetes, MLflow, Airflow, FastAPI
✔ Deploy ML models to production using CI/CD (GitHub Actions / Jenkins)
✔ Cloud-native MLOps — AWS, GCP, Azure, serverless & container deployments
✔ Automate workflows with Airflow & Kubeflow Pipelines
✔ Monitor production models — drift, performance, logs (Prometheus & Grafana)
✔ Version control datasets & models using DVC + MLflow Tracking
✔ Automated testing & validation for ML systems
✔ Build secure ML APIs & pipelines — governance, role-based access, encryption
✔ Work on real industry-grade projects (deployment API, retraining pipeline, scalable inference service)
✔ Job-focused skillset for MLOps Engineer, ML Engineer, AI DevOps Engineer roles
Transition Your Career To MLOps Now!
5000+ professionals have already transitioned and advanced their careers
Upcoming MLOps Training Batches
MLOps Live Online and Classroom Training
- Training Duration: 100+ hours of live, instructor-led MLOps training
- Course Length: 3-month structured learning program
- Training Mode: Live online sessions and classroom-based training
- Batch Schedule: Weekday and weekend batches available
- Refund Policy: Refund option available
10th January
FRIDAY
7:00 pm to 8:00 pm
(IST GMT +5:30)
11th January
SATURDAY
7:00 pm to 8:00 pm
(IST GMT +5:30)
13th January
MONDAY
8:00 pm to 9:00 pm
(IST GMT +5:30)
₹ 29,999 /-
|$ 445 USD
( all inclusive )
EMIs start at ₹ 5000 / month
( No cost EMI option available )
Secure Transaction
ML Ops Self Paced Training course
- Instant access to full ML Ops Course Recordings – Learn at your own pace, from anywhere, anytime
- No fixed class schedule – Study whenever it suits you with our ML Ops Self-paced Course
- Perfect for shift workers – Or ideal if you can't commit to a fixed class time
- Personalized trainer support – Get help with your doubts whenever you need it
₹ 29,999 /- | $ 445 USD
( all inclusive )
EMIs start at ₹ 5000 / month
( No cost EMI option available )
Secure Transaction
Industry-Standard MLOps Training Course
- Industry-Experienced Trainers with real production exposure
- 24×7 Dedicated Learner Support for guidance beyond classroom hours
- Modern LMS Access for recordings, labs, assignments, and progress tracking
MLOps Corporate Training Programs for Your Teams
Practical & Project-ready MLOps training customized for enterprise teams
ML Ops Trainer Profile
Nageswara Rao P
- Our best AWS DevOps trainer, Nageswara Rao P, is a seasoned professional with 17+ years of experience as a DevOps Architect, Consultant, and Corporate Trainer
- 11 years of experience as a trainer at Wiculty: Can simplify complex concepts simple with real-world anologies
- Former WalmartLabs employee: Brings practical industry experience to training sessions
- Passionate trainer: Understands what is required for learners to crack the interview and work on AWS DevOps real-world projects
- Trained 10,000+ students through AWS DevOps online, classroom, and corporate training programs
Take a Demo Now - Your DevOps Journey Begins Here!
Watch our Demo
ML OPs Projects Covered
GamutKart - E-commerce Platform (Similar to Flipkart)
In this DevOps hands-on project, you will build and deploy a fully functional e-commerce platform using AWS DevOps tools, CI/CD pipelines, Multiple test environments with Production setup, Load balancer and best practices. This AWS DevOps project simulates real-world e-commerce scenarios, helping you apply your AWS DevOps training skills in a practical setting
GuestBook - A Web-based Guestbook Application
In this project, you will build and deploy a GuestBook application that allows users to sign a virtual guestbook with their names and messages. This web application will demonstrate the core principles of AWS DevOps certification course, infrastructure automation, and containerization
Nginx Web Server Deployment & Configuration
In this hands-on project, you will deploy a static web application and configure an Nginx web server, demonstrating your AWS DevOps training skills through real-world infrastructure setup, continuous integration, and automated deployment processes
ML Ops Certification Course Training Curriculum
Module 1 DevOps – A Big Picture
- What is DevOps, Acronym What is Dev & Ops?
- Acronym: Dev + Ops – misconceptions.
- Gamut of Devops Tools overview
- End-to-End DevOps work-flow
- Roles and Responsibilities of DevOps Resource
- Who can learn DevOps?
- Pre-requisites for DevOps
- Importance of DevOps Practices in Software Development.
- DevOps in Realtime and it’s goals.
- SDLC models, Agile and DevOps
- History of DevOps
- Important terminology
- Opportunities, Trends and Future of DevOps
- Overview of: Version Control mechanism, Build and Deployment Process, Continuous Integration and Deployment, Configuration Management, Containerization, Virtualization, AWS Cloud platform, etc..
- Role of Cloud Platforms in DevOps
- DevOps and Cloud. Is Cloud + something is DevOps?
Module 2 Git - Version control system
Chapter 1 Version Control Systems Overview
- Introduction to Version Control Systems (VCS)
- Different Version Control Systems in the Market
- Evolution of Version Control Systems (VCS)
- Role of VCS in Source Code Management
- Goals of Version Control Systems
- Key Features of Version Control Systems
- Role of Version Control Systems in DevOps
- What is Git and Why Git? Role of Git in DevOps
- Role and Responsibilities of a DevOps Engineer in Git
- Source Code Versioning and its Role in Release Management
- Git Features – CVCS vs DVCS Explained
- Principles of Version Control Systems
Chapter 2 Getting started with Git
- Git Basics
- Git Architecture
- Evolution of Version Control Systems (VCS)
- Source Code Management with Git
- End-to-End Git Workflow (10,000 ft Overview)
- Git vs SVN vs Other Commercial VCS Tools
- Git Command Line (CLI) and GUI Tools
- On-Premise vs Hosted Git Solutions
- Overview of GitHub, GitLab, Bitbucket & Other Platforms
Chapter 3 Let’s make our hands Dirty with Git
- Git Installation, Uninstallation & Upgradation (Linux & Windows)
- Git Command Line & GUI Tools
- DevOps Engineers' Favourite – CLI or GUI?
- Mandatory Git Configurations & Best Practices
-
Using
$ git config– User, Email, Editor & Credential Setup - Creating Remote Repositories – On-Premise & GitHub
- Creating Local Repositories
- End-to-End Git Workflow Execution with Commands
Chapter 4 An attempt to Deep dive into Git concepts
- Understanding Git jargons based on what you've learned so far
- How much can you explain Git if you had to give a short lecture?
- Understanding Git as a tool & its internals
-
Commit your first change consciously —
git add,git commit,git push - What is Source, Stage & Local Repository?
- Git Revision Structure – SHA, User, Email, Commit Message & Metadata
- How Git generates SHA — checksum, data integrity & why hexadecimal?
- Significance of the Staging Index — and why Git allows skipping it
Chapter 5 Advanced Git. Let’s be more technical!
- Git command line with most frequently used options in real-time
- $ git log
- git log –author
- git log –grep
- git log –since
- git log –until
- git log –oneline
- git log –grep, etc.
- $ git diff
- git diff
- git diff –staged
- git diff sha..sha
- $ git rm
- Is deletion permanent? Best practices.
- Resurrect a deleted file
- $ git mv
- Renaming a file
- History carry forward after rename
- Listing the change efforts from repository
- Is deletion permanent? Best practices.
- Resurrect a deleted file
- Understand
git showoutput
- Undoing the changes
- Revert a change from Source Area
- Revert a change from Staging Area
- Revert a committed change
- $ git log
Chapter 6 Branching & Tagging –Release management with Git
- What is a branch & tag?
- When and why do we create a new branch and tag?
- Importance of master branch & stable code
- Branching Strategies or Models – Pros and Cons
- Practicals
- List all branches
- Creating a new branch and making it public
- List all remote branches
- Switching from one branch to another
- Create and switch to newly created branch
- Understanding HEAD and Git’s intelligence
- List all tags
- Creating tags and best practices
Chapter 7 Merging and Rebase
- What is merge?
- Merging best practices
- Merging vs Rebase
- Fast-Forward Merge
- 3-way Merge algorithm
- Merging from one branch to another
- Conflict resolution best practices
- Branching best practices to minimize conflicts
- Practicals
- Merging the code from one branch to another
- Conflict markers & resolution
- Identifying conflict owners
- Test your merge before you commit
- Reverse merging
Chapter 8 Remote Git
- Git pull
- Git push
- Git clone
- Git fetch
- Difference between pull and fetch
- Difference between clone and pull
- Pull and fetch best practices
Module 3 Maven Build Tool
Chapter 1 Overview of build tools
- Build and Deployment End-to-End Workflow
- Roles and Responsibilities of DevOps Engineer in Software Build & Deployment
- Role of Build Tools in Software Build Process Automation
- Introduction to Maven Build Tool
- Maven Vs ANT — Key Features of Maven Over ANT
- Build Tools for Different Languages
- Feel the Pain of Source Code Manual Compilation — Manual Example
- Necessity of Transforming Source Code into Binaries
- What is Compilation?
- Why Source Code Compilation is Required?
- Artifact, Binaries, Executables & Object Code — Terminology
- Machine vs Human Understandable Language
Chapter 2 Getting started with Maven
- Maven Installation and Prerequisites, Downloading Maven and JDK
-
Setting up
JAVA_HOME,M2_HOMEandPATHenvironment variables -
Understanding
$USER_HOME/.bashrcand installing tools in Linux - Java Build Process & Packaging Sequence (.class, .jar, .war, .ear, etc.)
- TEST YOUR KNOWLEDGE BEFORE DEEP DIVE:
- What is compilation & why do we compile the source code?
- Packaging sequence for a Java application
- What is Build?
- What is Deployment?
- What is an Environment?
- Dev, QA & DevOps Teams — Interaction and Collaboration
Chapter 3 How to collaborate well with DEV and QA teams
- Creating a project using Maven
- Maven’s “Convention over Configuration” feature
- Understanding Project Source Tree Layout
- Understanding JUnit Unit Testing Framework
- Understanding Test Driven Development (TDD) Approach
- Overview of Software Development & Other Testing Methodologies
- Software Development & Testing Best Practices
Chapter 4 Hands-on with Maven
- Building your first project
-
$ mvn installcommand & deep discussion about Maven lifecycle phases - Understanding build output, test results, class files etc.
-
Verifying built artefacts, naming convention and
.m2local repository - Dependency Management: What is code dependency – Maven’s automatic dependency resolution feature
-
Direct and Transitive Dependencies – Defining dependencies in
pom.xml - Maven binary repositories – Local, Private and Central repository
Chapter 5 Implementing various Build methodologies based on real-time requirements
- Build Types – Hands-on
- Complete Build / Clean Build / Full Build
- Nightly Build
- Daily Build
- Bugfix Build
- Adhoc / Unplanned / Emergency Builds
- Execution of all build types with hands-on for GamutKart project
- Maven plugins, skipping test compilation & running tests only when required
-
$ mvn install -DskipTests -
$ mvn install -Dmaven.test.skip=true -
$ mvn surefire:test - Creating project for web application & building the WAR file
Chapter 6 Deployments deep dive
- Understanding Various Environments & Their Usage: DEV, QA, SIT, UAT, PERF, STAGE, PROD, etc.
- Deployment Promotion Methodologies (Moving Code from One Environment to Another)
- Understanding Application Servers vs Web Servers
- Tomcat Installation & Configuration
- Understanding Tomcat Startup Scripts, Deployment Path & Port Configurations
- Building & Deploying GamutKart Project into Tomcat
- Understanding WAR / EAR Files & Their Internal Resources
Chapter 7 Projects
- Project-1: Automate Complete Build & Deployment Process Using Maven and Shell
- Project-2: Automate Build & Deployment for Real-Time GamutKart Application
- Deployment Best Practices & Rollback Process
- Launching Applications from Different Environments
- Understanding DEV, QA, OPS & DEVOPS Teams Interactions, SLAs & Support
- Introduction to CI/CD Process to Reduce Deployment Turn-Around Time
Module 4 Linux/Unix
Chapter 1 Learn Linux Admin Level?
- Learn Package Management & Process Monitoring
- Work on Services, Utilities, Important Files & Directories
- Understanding SystemD Functions & How It Works
- Linux User Administration Functions
- File System Management (Generic & LVM)
- Advanced File System Management (Software RAID)
- Control Server-Client Configurations (FTP / SFTP / HTTP)
- Configuring Samba & SMTP Servers
- Firewall, IP Tables & Security Checks
- Database Configuration (MySQL / MariaDB)
- Using Control Panels to Manage Linux Servers (Webmin)
Module 5 Shell Scripting
Chapter 1 Introduction to Shell Scripting
- What is a Shell?
- Importance of Shell Scripting
- Common Shells: Bash, Zsh, Fish
- Basic Syntax & Structure of Shell Scripts
- Creating & Running Your First Shell Script
Chapter 2 Basic Shell Commands
-
File Operations:
ls,cd,pwd,mkdir,rm -
Text Processing Commands:
cat,grep,sed,awk -
System Information Commands:
uname,top,ps -
File Permissions:
chmod,chown - Pipelines & Redirection
Chapter 3 Variables and Data Types
- Variable Declaration & Assignment
- Environment Variables vs Local Variables
- Data Types: Strings, Integers, Arrays
- Command Substitution
- Arithmetic Operations
Chapter 4 Control Structures
- If-Else Statements
- Case Statements
- For Loops
- While Loops
- Until Loops
- Break & Continue Statements
Chapter 5 Functions
- Function Declaration Syntax
- Passing Arguments to Functions
- Return Values and Exit Status
- Local vs Global Variables in Functions
- Recursive Functions
Chapter 6 Input/Output Operations
- Reading user input with read
- Command-line arguments
- Redirecting input/output
- Piping commands
- Here documents
Chapter 7 File Operations and Text Processing
- Reading from and writing to files
- Text processing with sed and awk
- File permissions and ownership
- Finding and manipulating files with find
- Archiving and compression
Chapter 8 Regular Expressions
- Basic regex patterns
- Using regex with grep and sed
- Extended regular expressions
- Regex in Bash scripting
- Practical regex example
Chapter 9 Debugging and Error Handling
- Using set -x for debugging
- Error handling with exit codes
- Trapping signals
- Logging and error reporting
- Debugging techniques and best practices
Chapter 10 Advanced Topics
- Using set -x for debugging
- Error handling with exit codes
- Trapping signals
- Logging and error reporting
- Debugging techniques and best practices
Chapter 11 Best Practices and Security
- Code organization and commenting
- Security considerations in shell scripting
- Performance optimization techniques
- Version control for shell scripts
- Deploying and maintaining shell scripts
Module 6 Jenkins – Continuous
Chapter 1 Jenkins concepts Overview
- Introduction to Agile Development
- Definition of continuous integration (CI), continuous delivery (CD), continuous deployment (CD)
- Difference between CI and CD
- End-to-End CI & CD Phases
Chapter 2 Getting started with Jenkins (Installation & Production Set-up)
- What is Jenkins and Why Jenkins
- Understanding continuous integration
- Introduction about Jenkins
- Jenkins Features
- Build Cycle
- Jenkins Architecture
- Production Installation and Configuration
- Tomcat and JDK installation. Setting up environment variables.
- Installing and configuring Jenkins using WAR and RPM
- Java installation and configuration
- Maven Installation
- Exploring Jenkins Dashboard
Chapter 3 Let’s make our hands Dirt with Jenkins (Hands-on)
- Creating Jenkins job/project for builds integrating Git and Maven
- Usage of different Job configuration options
- Different types of Jenkins Jobs
- Use cases for Freestyle, Pipeline, multi-configuration projects
- Configuring automated Build for WAR package creation
Chapter 4 Manage Jenkins
- Configuration of tools installations for Maven, JDK, etc.
- Jenkins global configurations and settings
- All options in Manage Jenkins
Chapter 5 Setting up Builds
- What are the different build types available in Jenkins?
- Build tools configuration in Manage Jenkins
- Jenkins job build steps, triggers, artefacts, and repositories
- Setting up build steps and triggers
- Build tools configuration
- Running scripts as part of build steps
- Integrating source code management tools and polling VCS to achieve C.I/C.D
- Develop automation for QA, SIT, UAT, and PROD environment deployments
- Write deployment scripts for different environments
Chapter 6 Jenkins Pipelines - Deep dive & advanced concepts
- What is pipeline?
- Advantages of build pipelines
- Creating pipeline projects using GUI
- When to use pipelines and different types of pipelines
- Manual/GUI pipeline Vs Jenkins’ file scripted pipeline
- Upstream/downstream jobs
- Writing Jenkins file using Groovy
- Groovy scripts and syntax
- Creating pipeline projects using Jenkins file and declarative Groovy DSL
Chapter 7 Parameterized Jenkins jobs
- Creating Parameterized build jobs
- Passing parameters between jobs
- Identifying parameters and how to use them: file parameter, string parameter, choice parameter
- Deployments to QA, SIT, UAT, etc environments using a single Jenkins job
- Writing Shell script to deploy the application into multiple machines of any environment
Chapter 8 Jenkins CLI - Command line options
- Use cases and applying Jenkins CLI for real-time scenarios
- Explore Jenkins CLI options
- Triggering build jobs from commandline
- Cleaning up builds runs using CLI
- Running Jenkins CLI based on user’s authorizations
Chapter 9 Jenkins Plugins
- Introduction to Plugins. What is a plugin?
- Plugins Installation, Un-installation and upgrade
- Different ways of plugin installation and management
- Most Frequently used plugins in real-time (10 – plugins usages)
- Finding suitable plugins and interpreting plugins documentation for real-time scenarios
Chapter 10 Jenkins Administration
- Changing Jenkins HOME directory
- Setting up System notifications for users
- Email configuration for sending CI/CD notifications
- Setting up different notifications for build, deployment, testing failures
- Jenkins backup mechanisms and restoration policies
- Installation of thin backup plugin and configuring the same for automatic backups
- Setting-up HA and Test server for Jenkins
Module 7 Docker -- Containerization
Chapter 1 Introduction to Containerization & Docker
- What is containerization?
- What is Docker?
- Why Docker and Docker features, who can use it?
- Basics of Virtualization
- Difference between Virtual machine (VM), Physical machine and Docker container
- Virtual machine and Docker usage in real-time and DevOps world
Chapter 2 Docker Installation in Production
- Docker supported platforms
- Docker pre-requisites in production
- Pre-requisites check commands (OS, Kernel, Hardware, etc.)
- Docker Installation Steps
- Configuring Docker to be executed without sudo
- Installation check
- Docker clean uninstallation
Chapter 3 Getting started with Docker containers
- Creating first container & Linux concepts and features for containers
- Root file system, networking and processes isolation
- Docker hardware and OS lightweight virtualization
- Docker image concepts. Shipping the product code with dependencies and pre-requisites
- Installation of frequently used Linux commands (ssh, net-tools, vim, etc.)
- Difference between Docker Image and Container
- Inspecting the new container (hostname, IP, hosts file, processes, networking capabilities)
- How Docker creates any flavour of container on top of any host Linux OS
- Creating Linux containers on Windows. Concepts involved
- SSH setup in containers
Chapter 4 Container management commands
- Shutdown Docker container
- Listing all containers in host
- Listing only running containers
- Listing last few number of containers
- Inspecting Docker container information
- Listing last created container
- Creating a container with our own name
- Renaming a container
- Deleting one, all, stopped and running containers
Module 8 Kubernetes – Container
Chapter 1 Introduction to Kubernetes & Kubernetes concepts
- Why do we need Kubernetes
- Pods
- Replica Sets
- Deployments
- Services
- Kube-DNS
-
Nodes:
- Kublet
- Proxy
- Docker
-
The Master node:
- ETCD
- The API Server
- The scheduler
-
Available tools:
- Kubectl
- Dashboard
- Minikube
Chapter 2 Kubernetes Installation & Setup in Local and Production
- Local Kubernetes setup with Minikube
- Starting up the local Kubernetes cluster
- Installing Kubectl
- Production Kubernetes setup using Kubeadm
Chapter 3 Advanced Docker concepts, helps understanding Kubernetes effectively
- Docker Networking
- Networking commands
- Creating and inspecting a network
- Connecting a container to the network
- Exposing ports and mapping ports
- Persistent storage
- Volume-related commands
- Creating a volume
- Removing a volume
Chapter 4 Working with Microservices
- Creating Service
- Creating Deployment
- Autoscaling and manual scaling
- Interacting with Containers and logs viewing
- Using Kubernetes dashboard
Chapter 5 Advanced Kubernetes: Deploying on the Kubernetes cluster
- Creating Service
- Creating Deployment
- Autoscaling and manual scaling
- Interacting with Containers and logs viewing
- Using Kubernetes dashboard
Chapter 6 Project: Kubernetes features implementation for Gamut kart project
- Creating Services
- Creating deployments for Gamut kart project
- Autoscaling environment for Gamut kart
Module 9 Ansible - Configuration
Chapter 1 Introduction to Configuration Management with Ansible
- Introduction to Ansible
- Configuration Management
- Ansible History
- How Ansible Works
- Data Flow
Chapter 2 Understanding the Ansible Framework
- Case Study
- Ansible way of Configuration Management
- Infrastructure as a code
- Idem potency
- Ansible Terminology
Chapter 3 Ansible Deployment
- Ansible Architecture
- Pre-Requisites for controller Node
- Test Environment Setup
- Installation and configuration
- Ansible Configuration file
- Pre-Requisites for Managed Node
- Ansible Inventory
- Ansible Communication
- Communication checks with password Authentication
- Communication with key-Based Authentication
- Overriding the Default HOSTS File
- The Default System Ansible.Cfg File
- Overriding the Default Roles Path
Chapter 4 Ad-Hoc Execution with Ansible
- Ansible Modules
- Ad-Hoc Remote Executions
- Ansible commands
- Connection and Privilege Escalations
Chapter 5 Ansible Playbooks
- YAML Structure
- Playbook structure
- Ansible playbooks
- Playbook syntax checks
- Playbook Smoke tests
- Playbook Real-time run
- Playbook examples
Chapter 6 Variables in Ansible
- Defining Variables in Ansible Code
- Use Cases
- Ansible Facts
- System Facts: Common Values for Playbooks
- Facts in Playbooks
- Disabling Facts
Chapter 7 Conditional, Loops and Handlers
- Conditionals in Ansible
- Loops in Ansible
- Handlers in Ansible
Chapter 8 Ansible Vaults
- Introduction
- Real-Time example with Ansible Vault
Chapter 9 Ansible Includes
- Basic Include Statements
- Includes – Breaking Your Playbook into Discrete Plays
Chapter 10 Ansible Playbook Optimization
- Copy and Fetch Modules
- Facts
- Forks
- Serial & Max_Fail_Percentage
- Asynchronous Action and pooling
- Delegate To
- Ignore Failed commands/Basic Error Handling
- Tags
- Jinja2 Templates
- Dry-Run
- Simple Variable Substitution
- Lookups
- RunOnce
- Local Actions
- Notify
- Prompt – Interactive Playbook
- Starting At Task or Stepping Through All Tasks
- Passing Variables Into Playbooks at the Command Line
Chapter 11 Ansible Roles
- Introduction
- Directory Structure
- Role creation
- Include and Dependency Management
Chapter 12 Ansible Tower
- Introduction
- Tower installation
- Tower Dashboard
Chapter 13 Ansible Modules
- ‘Setup’ Module
- The ‘File’ Module
- ‘Pause’ Module
- ‘WaitFor’ Module
- ‘Yum’ Module
- ‘Apt’ Module
- ‘Service’ Module
- ‘Copy’ Module
- ‘Command’ Module
- ‘Cron’ Module
- ‘Debug’ Module
- ‘Fetch’ Module
- ‘User’ Module
- ‘AT’ Module
- ‘DNF’ Module
- ‘Apache2_Module’ Module
- ‘SetFact’ Module
- ‘Stat’ Module
- ‘Script’ Module
- ‘Shell’ Module
- ‘SELinux’ Module
- ‘SEBoolean’ Module
- ‘Raw’ Module
- ‘Ping’ Module
- ‘Unarchive’ Module
- ‘HTPasswd’ Module
- ‘GetURL’ Module
- ‘Group’ Module
- ‘Mail’ Module
- ‘Filesystem’ Module
- ‘Mount’ Module
- ‘Notify’ Module
- ‘AptRepo’ Module
- ‘AptKey’ Module
- ‘ACL’ Module
- ‘Git’ Module
- ‘Template’ Module
- ‘MySQL_DB’ Module
- ‘MySQL_User’ Module
- ‘Kernel_Blacklist’ Module
Module 10 AWS - Cloud Platform
Chapter 1 Introduction to AWS
- History of AWS
- What is virtualization?
- Virtualization and cloud computing
- Types of virtualization
- Virtualization terminologies
- Hypervisor
Chapter 2 Compute EC2
- Cloud Computing
- Introduction to Cloud Computing
- Why Cloud Computing?
- Benefits of Cloud Computing
- Types of Cloud Computing
- Public Cloud
- Private Cloud
- Hybrid Cloud
- Community Cloud
- Software as a Service
- Platform as a Service
- Horizontal vs. Vertical scaling
- Cloud Computing Issues
Chapter 3 EBS (Elastic Block Storage)
- About AWS EBS (Elastic Block Storage)
- Create EBS volumes
- Delete EBS Volumes
- Attach and detach EBS volumes
- Mounting and un-mounting EBS volume
- Creating and deleting snapshots
Chapter 4 Understanding AMI
- Launching your first AWS instance
- On-demand Instance pricing
- Reserved Instance pricing
- Spot instance pricing
- Setting up security
- Security groups
- Choosing the AMI
- Creating a new AMI
- Public and Private IP’s
- Deploying a new instance from the created AMI
- Key Pairs
- Elastic IP’s
Chapter 5 ELB(Elastic Load Balance)
- Load-Balancer
- Create an Application Load Balancer
- Create a Network Load Balancer
- Create a Classic Load Balancer
Chapter 6 S3 (Simple Storage Service)
- S3 Buckets
- S3 durability and redundancy
- S3 Uploading Downloading
- S3 Permissions
- S3 Object Versioning
- Static Web hosting
- S3 Lifecycle Policies
- Backup
Chapter 7 IAM (Identity Access Management)
- Creating Users and Groups
- Applying policies
- Password Policy
- Roles
- MFA
- Encryption Keys
- Identity Provider
- Amazon Virtual Private Cloud (VPC)
- What is VPC?
- VPC configuration
- VPC security
- Elastic IP’s, Inbound and outbound ACL’s
- VPC Peering
- VPN S/W
Chapter 8 Route 53
- Creating zones
- Hosting a website
- Understanding routing policies
- Weighted, simple and failover policies
Chapter 9 Cloud Watch
- Cloud Watch dashboard
- Configuring Monitoring services
- Configuring actions
- Creating a Cloud Watch alarm
- Getting statistics for EC2 instances
- Monitoring other AWS services
- Configuring Notifications
Chapter 10 Cloud Front
- Use of CloudFront
- Creating a CloudFront distribution
- Hosting a website via CloudFront distribution
- Implementing restrictions
- Configuring origins and behaviors
Chapter 11 RDS
- Selecting the Database type
- Configuring the database
- Creating database
- Configuring backups
- Configuring the maintenance windows
- Connecting to the database
Module 11 Terraform - Infrastructure as Code
Chapter 1 Introduction to Terraform
- What is Infrastructure as Code?
- Introduction to Terraform
- Terraform vs. other IaC tools
- Installing Terraform
- Terraform workflow
Chapter 2 Terraform Basics
- Terraform configuration language
- Providers and resources
- Variables and outputs
- Data sources
- Terraform state
Chapter 3 Terraform and AWS
- Setting up AWS provider
- Creating EC2 instances
- Managing VPCs and subnets
- Working with S3 buckets
- Creating and managing IAM roles
Chapter 4 Terraform Modules
- Understanding Terraform modules
- Creating reusable modules
- Module inputs and outputs
- Using public modules from Terraform Registry
- Best practices for module organization
Chapter 5 Terraform State Management
- Understanding Terraform state
- Local vs. remote state
- State locking
- Using S3 backend for remote state
- Workspace management
Chapter 6 Terraform and Azure
- Setting up Azure provider
- Creating Azure VMs
- Managing Azure Storage accounts
- Working with Azure App Services
- Azure Resource Groups and Networking
Chapter 7 Terraform Best Practices
- Code organization and structure
- Naming conventions
- Version control integration
- Managing secrets and sensitive data
- Terraform style guide
Chapter 8 Terraform and Google Cloud Platform
- Setting up GCP provider
- Creating GCP Compute instances
- Managing GCP Storage buckets
- Working with GCP Networking
- GCP IAM and service accounts
Chapter 9 Advanced Terraform Techniques
- Terraform functions
- Dynamic blocks
- Terraform loops and conditionals
- Data manipulation with Terraform
- Using Terraform console
Chapter 10 Terraform Testing and Validation
- Writing and running Terraform tests
- Using terraform validate
- Automated testing with Terratest
- Policy as Code with Sentinel
- Compliance and security checks
Chapter 11 Terraform Cloud and Enterprise
- Introduction to Terraform Cloud
- Remote operations and collaboration
- Private module registry
- Terraform Enterprise features
- Integrating with CI/CD pipelines
Chapter 12 Terraform and Kubernetes
- Managing Kubernetes clusters with Terraform
- Deploying applications to Kubernetes
- Helm charts integration
- Managing Kubernetes resources
- Multi-cloud Kubernetes deployments
Chapter 13 Terraform for Multi-Cloud Deployments
- Strategies for multi-cloud management
- Creating provider-agnostic modules
- Managing state across multiple clouds
- Cost optimization in multi-cloud environments
- Disaster recovery and high availability
Chapter 14 Terraform and DevOps Practices
- Integrating Terraform with GitOps workflows
- Continuous Integration and Continuous Deployment
- Infrastructure monitoring and logging
- Automating infrastructure updates
- Disaster recovery planning with Terraform
100+ Hours of In-Depth MLOps Training
While many programs focus on quick overviews, our curriculum ensures deep understanding, practical mastery, and job-ready MLOps skills.
ML Ops Engineer Certification Course and Placement Approach Flow
Concepts & Theory
You will first learn the ML Ops concept & theory of each topic clearly, with real-time use cases and analogies followed by doubt clarifications.
Practicals
Next, you will practically execute the ML Ops concepts in a simulated real-time environment gaining hands-on experience.
Project Work
You will then apply topic specific practicals to real-time projects and automate work-flows.
Interview Preparation
We will discuss common interview questions and answers related to the topic you have learned, preparing you to confidently face ML Ops interviews.
Resume Building & Placements
Upon completion of the ML Ops course, we will assist you with resume building and provide ML Ops job placement support.
After Job Support
Even after your placement, we will continue to support you with your real-time tasks & be part of your ongoing ML Ops learning journey and ML Ops Engineer career growth.
Industry-Recognized MLOps Course Completion Certificate
What certificate will I receive after completing the MLOps course?
- You will receive an Industry-Standard MLOps Course Completion Certificate from JingleAIAcademy after successfully completing the course requirements, including assignments and projects.
Is this certificate useful for jobs and interviews?
- Yes. This certificate validates your practical MLOps skills, real-world project experience, and hands-on training—making it valuable for resumes, LinkedIn profiles, and job interviews.
Is this a certification or a course completion certificate?
- This is a course completion certificate, not a third-party vendor certification. It demonstrates that you have completed structured, industry-aligned MLOps training with practical exposure.
Complete ML Ops Training and Placement Solutions.
All In One Place!
(Leverage our 10 Yrs. of Industy Expertise)
Why choose Jingle AI Academy : MLOps Course over other institutes?
- 100+ Hours of In-Depth, Comprehensive MLOps Training – Jingle AI Academy makes learning clear and effective!
- Hands-on MLOps Training with 3 Real-time Projects
- 17+ Yrs Experienced In-house DevOps Trainer, Nageswara Rao, DevOps Architect
- Focussed on Practical, Technical Excellence
- MLOps Job-Oriented Training & Career-Ready Program
- Includes Trending Skill DevSecOps & Industry best AWS DevOps practices
- After the MLOps training course, you gain Experience which is equal to 4-5 Yrs. Real-time Experienced professional
- Trained More Than 10000+ learners & 6000+ Placement Record
- Dedicated & Exclusive MLOps and Cloud certification Learning institute. So We are Lasor focused In The Field
- Jingle AI - Wiculty has 11 Yrs. Of Experience In Only AWS DevOps & Cloud certification Training
- Wiculty has 11 Yrs. Of Experience In Only AWS DevOps & Cloud certification Training
- Complete Support: Training, Interview Preparation, Documentation, Placement Assistance, and Post-Course Job Support
- Trainer is Accessible for Guidance and Support Throughout the Course
- Many other Institutes offer 40-45 Hrs short-term, highlevel AWS DevOps courses
- Most of the other institutes offer Theoreotical / Slide based training with No hands-on & Projects.
- Less experienced & Outsourced Trainers
- Marketing & Business-Centric content & High-Level Training
- Generic Training & No support after training
- More traditional curriculum
- Suitable for Freshers & Managers Who Just Want To Know What Is What
- Less Experienced & no focus on placements
- Other institutes usually provide training for all courses. So, Not focused and don’t have expertise
- Less Experienced
- Only Training or specific services
- Trainers are usually Not Reachable. . Mostly, support is reachable
Who Can Take The AWS DevOps Training Course?
- Individuals seeking domain change
- IT Operations Engineers
- System | Linux Administrators
- Cloud Engineers/Architects
- Aspiring DevOps Engineers
- Infrastructure Engineers
- Software Developers & Testers
- IT Managers & Technology Leads
- Project | Product | Release Managers
- IT Support & Desktop Technicians
- Application | Production Support
- New College Graduates
- Individuals trying to get into Software field
Master the MLOps Stack: From GitOps to Kubeflow.
Automate pipelines and orchestrate containers for seamless ML lifecycles.
ML Ops Training Course Completion Benefits
Shift to ML Ops - Move into high-demand ML Ops or AI Engineering roles with confidence.
Job-Ready Skills - Master the exact tools and workflows needed to crack ML Ops interviews.
Hands-On Project Experience - Work on real-time ML pipelines, deployments, and monitoring from day one.
High-Growth Career Path - Unlock better salary, long-term stability, and top-tier opportunities in AI.
Certification Support - Prepare for leading ML/AI and cloud certifications aligned with ML Ops.
Resume & Placement Help - Get resume polishing, mock interviews, and placement assistance to land your ML Ops job faster.
Our Alumni Placed In Leading AWS DevOps Roles
We understand your career goals, whether you’re looking to upskill in AWS DevOps domain, or transition into a DevOps Engineer role. Our AWS DevOps training course provides a clear path, offering the best AWS DevOps real-time training to help you land your DevOps job
ML Ops Training Course Reviews
RITHIK CHINDUKURI
This is very good institute for devops for fresher as well as for working professionals.Trust me trainer nageshwararao adds value to your knowledge he is very patient and explains every devops concept theoretically as well as practically.join this institute without second thought to gain good knowledge in devops.
20E11A6635 Venkat Sai
100% Placement Assistance & Job Gurarantee Programs
(Take advantage of our Client Network For Success)
ML Ops Course FAQs
What is the eligibility for the AWS DevOps Training Course? Do I need to have any programming or linux experience?
- There are no specific prerequisites for enrolling in our AWS DevOps training course. We start with the basics of Linux and take you to an advanced level. Programming experience is not required.
I am from a Civil, Mechanical, EEE, ECE ..etc. non computer science background. Can I take this AWS DevOps course?
- Yes. According to LinkedIn, Glassdoor, StackOverflow, TechNation, approximately 40-50% of software professionals are from non-computer science degrees. So, you can become DevOps Engineer
I am a fresher. Can I take the AWS DevOps course?
- Yes, absolutely! Our AWS DevOps training course is designed for freshers as well as professionals looking to switch careers or enhance their skills
Do you offer both online and classroom AWS DevOps training courses?
- Yes, we offer both online and classroom training options for our AWS DevOps course
What is the course duration & length?
- The AWS DevOps course at Wiculty is a 100+ hour program, designed to be completed in approximately 3-4 months. However, if you’re looking to fast-track your learning, we offer flexible options to attend multiple batches
How do I practice?
- We guide you through setting up the required local and cloud labs. We also provide comprehensive practice materials, Project work documentation, Interview preparation resources and related books in soft copy format
What is your fee refund policy?
- At Wiculty, we strive to ensure complete satisfaction with our AWS DevOps training course. However, you can receive a full refund even after attending up to 10 classes
Who is the trainer, and what is their experience?
- Our AWS DevOps trainer, Nageswara Rao P, is a highly experienced DevOps Architect and Corporate Trainer with over 17 years of industry experience, including 11 years as a trainer. He has successfully trained 15,000+ students in AWS DevOps and related fields
Are real-time projects included in the course?
- Our AWS DevOps training is entirely real-time and hands-on. No theory or slide-based learning. You will work on 3 real-world projects. AWS DevOps course includes hands-on exercises, project work, interview questions, and industry best practices
Do you provide certification?
- Yes, upon successful completion of the AWS DevOps training course, you will receive a course completion certification from Wiculty. You will be also fully prepared to take the AWS Certified DevOps Engineer – Professional (DOP-C01) exam
Do you provide placement support?
- Yes, having been in the AWS DevOps training industry for over 11 years, we have built strong relationships with a wide network of clients who come to us for AWS DevOps placements
Do you provide post-job support?
- Yes, we provide post-job support even after you secure your role as an AWS DevOps Engineer
Is DevOps a job-fetching technology?
- I'm confused about which course to choose? Yes, DevOps is indeed a job-fetching and one of the emerging & trending technologies. It is in high demand across various industries. Many tech giants, startups, and MNCs are actively hiring AWS DevOps Engineers and Cloud Engineers
How much package can I expect after completing the AWS DevOps course?
- My current package is low.> Entry-Level (0-2 years) – ₹5-8 Lakhs> Mid-Level (2-5 years) – ₹8-15 Lakhs> Senior-Level (5-8 years) – ₹15-25 Lakhs
I want to change my domain from support or onother software field to DevOps Engineer. Is it a good decision?
- Yes, transitioning to DevOps Engineer is an excellent decision, especially considering the growing demand, job stability, better package, career growth for DevOps professionals
I have gaps after my degree. Can I take this AWS DevOps training course?
- Yes, absolutely! Having gaps in your career doesn’t disqualify you from taking the AWS DevOps course or pursuing a career in DevOps
Know Someone Struggling to Find a Job?
Refer Them and Earn a Bonus!
(We Guarantee Their Success)
ML Ops Course Related Blogs
ML Ops Interview Questions
Landing your dream MLOpsrole just got easier.
JingleAI Academy provides the comprehensive resources and curated insights you need to confidently navigate and succeed in any job interview.
Money-Back Guarantee – Enroll Risk-Free!
Not Satisfied? Get a Full Refund Before 10 Classes
