Udemy

MLOps with AWS - Bootcamp - Zero to Hero Series

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  • 10,067 Students
  • Updated 11/2025
4.5
(1,072 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Language
English
Taught by
Manifold AI Learning ®
Rating
4.5
(1,072 Ratings)
1 views

Course Overview

MLOps with AWS - Bootcamp - Zero to Hero Series

Empower Your MLOps Journey: AWS AI/ML Mastery - From Notebook to Production Operation with Expert Guidance - MLOps 2024

Welcome to "Practical MLOps for Data Scientists & DevOps Engineers with AWS"

Are you ready to propel your career in artificial intelligence and machine learning (AI/ML) development or data science to new heights? This comprehensive course is meticulously crafted for individuals with aspirations to excel in these domains, providing a Production Level mindset that goes beyond the basics.

Course Overview: Mastering MLOps with AWS

**1. Elevate Your Skills:

  • Design, build, deploy, optimize, train, tune, and maintain ML solutions using AWS Cloud.

  • Adopt a Production Level mindset tailored for Machine Learning in conjunction with DevOps best practices.

**2. Beyond Basics:

  • Employ model-training best practices on extensive cloud-based datasets.

  • Demonstrate expertise in deployment best practices for consistent functionality.

  • Implement operational best practices to guarantee zero downtime.

**3. Structured Learning Path:

  • Follow a logical, structured path with in-depth explanations, practical exercises, and relevant demonstrations.

  • Gain proficiency in tackling real-world business challenges by implementing scalable solutions on AWS.

Course Structure: Journey Through Mastery

Section 1: Introduction to the AWSMLOPS Course and Instructor

  • Get acquainted with the course objectives and the experienced instructor leading the way.

Section 2: Understanding MLOps

  • Delve into the core concepts of MLOps, understanding its significance and application.

Section 3: DevOps Principles for Data Scientists

  • Explore the principles of DevOps tailored for data scientists, bridging the gap between development and operations.

Section 4: Getting Started with AWS

  • Acquaint yourself with the AWS platform, laying the foundation for subsequent sections.

Sections 5-16: In-Depth Exploration

  • A comprehensive exploration of key topics, including AWS CodeBuild, AWS CodeDeploy, AWS CodePipeline, Docker Containers, Amazon SageMaker, Feature Engineering, SageMaker Pipelines, and much more.

Hands-On Learning: Real-World Applications

Tools and Technologies Covered:

  • Data Ingestion and Collection

  • Data Processing and ETL (Extract, Transform, Load)

  • Data Analysis and Visualization

  • Model Training and Deployment/Inference

  • Operational Aspects of Machine Learning

  • AWS Machine Learning Application Services

  • Notebooks and Integrated Development Environments (IDEs)

  • Version Control with AWS CodeCommit

  • Amazon Athena, AWS Batch, Amazon EC2

  • Amazon Elastic Container Registry (Amazon ECR), AWS Glue

  • Amazon CloudWatch, AWS Lambda

  • Amazon S3 for Storage and Scalability

Access to Course Materials:

  • All course materials, including source code, are available on GitHub for convenient access from anywhere.

  • Stay updated with the latest advancements through easy access to the latest updates.

Embark on the MLOps Journey: Elevate Your Skills Today

Why Choose This Course?

  • Gain a Production Level mindset tailored for AI/ML in conjunction with DevOps practices.

  • Acquire proficiency in deploying solutions on scalable datasets beyond personal laptops.

  • Comprehensive exploration of AWS services crucial for MLOps.

  • Real-world applications and hands-on projects for practical learning.

Your Success in MLOps Begins Here:

  • Equip yourself with the latest tools and best practices on the AWS platform.

  • Tackle complex business challenges with confidence.

  • Propel your career to new heights in the world of MLOps.

Enroll Now: Take the leap into mastering MLOps with AWS. Click the "Enroll Now" button to embark on a transformative learning journey. Elevate your AI/ML and DevOps skills to the next level and solve complex business challenges effectively. Your success in the world of MLOps begins here and now!

Course Content

  • 10 section(s)
  • 187 lecture(s)
  • Section 1 About AWS MLOps Course and Instructor
  • Section 2 Introduction to MLOps
  • Section 3 DevOps for Data Scientists
  • Section 4 Getting Started with AWS
  • Section 5 Linux Operating System for DevOps and Data Scientists
  • Section 6 Source code Management using GIT - CodeCommit
  • Section 7 Source code Management using GIT - Github
  • Section 8 YAML Crash Course
  • Section 9 AWS CodeBuild
  • Section 10 AWS Code Deploy

What You’ll Learn

  • Configuring the CI/CD Pipeline for Machine Learning Projects
  • Ability to track the source code & training images, configuration files with Git Based Repository – AWS CodeCommit
  • Ability to Perform the Build using AWS CodeBuild
  • Ability to Deploy the Application on Server using AWS CodeDeploy
  • Orchestrate the MLOps steps using AWS CodePipeline
  • Identify appropriate AWS services to implement ML solutions
  • Perform the Load testing
  • Monitoring the End Point Performance
  • Monitoring the Model Drift
  • The ability to follow model-training best practices
  • The ability to follow deployment best practices
  • The ability to follow operational best practices


Reviews

  • S
    Shashank Byalla
    4.5

    Good but need more on Practical side as of now!!

  • N
    Nivesh Jain
    4.0

    theory was too much till now , but I guess on this point onwards , there would be practical as well

  • K
    Kavya Gupta
    5.0

    Very structure course.

  • S
    Sarvesh R
    4.0

    excellent

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