24 Hrs
3665+ Enrollments
MLOps Engineering on AWS
This course provides hands-on training in the latest MLOps technologies on AWS. You'll learn how to develop and deploy scalable, fault-tolerant machine learning models in production environments. Additionally, this course covers the use of advanced AWS tools for data processing, storage, and analytics.
24 Hrs
3665+ Enrollments
MLOps Engineering on AWS
AWS MLOps
Overview of Course
The "MLOps Engineering on AWS" course is designed to provide a comprehensive understanding of machine learning operations on AWS. This course covers the core principles of MLOps, including model training, deployment, and monitoring using AWS services.
Course Highlights
Learn from experienced AWS certified trainers
Hands-on experience with real-world MLOps use cases
In-depth coverage of AWS services
Key Differentiators
Personalized Learning with Custom Curriculum
Training curriculum to meet the unique needs of each individual
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Trusted by over 100+ Fortune 500 Companies
We help organizations deliver right outcomes by training talent
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Flexible Schedule & Delivery
Choose between virtual/offline with Weekend options
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World Class Learning Infrastructure
Our learning platform provides leading virtual training labs & instances
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Enterprise Grade Data Protection
Security & privacy are an integral part of our training ethos
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Real-world Projects
We work with experts to curate real business scenarios as training projects
Skills You’ll Learn
#1
Designing and implementing machine learning models on AWS
#2
Building scalable and fault-tolerant machine learning systems
#3
Applying DevOps best practices to machine learning workflows
#4
Using AWS services for data processing, storage, and analytics
#5
Monitoring and optimizing machine learning models in production
Training Options
Corporate Training
On Request
Everything in 1-on-1 Training plus- Custom Curriculum
- Extended access to virtual labs
- Detailed reporting of every candidate
- Projects and assessments
- Consulting Support
- Training aligned to business outcomes
For Corporates
Unlock Organizational Success through Effective Corporate Training: Enhance Employee Skills and Adaptability
- Choose customized training to address specific business challenges and goals, which leads to better outcomes and success.
- Keep employees up-to-date with changing industry trends and advancements.
- Adapt to new technologies & processes and increase efficiency and profitability.
- Improve employee morale, job satisfaction, and retention rates.
- Reduce employee turnovers and associated costs, such as recruitment and onboarding expenses.
- Obtain long-term organizational growth and success.
Course Reviews
Curriculum
- Machine learning operations
- Goals of MLOps
- From DevOps to MLOps
- ML workflow
- MLOps view of ML workflow
- MLOps cases
- Intro to build, train, and evaluate machine learning models
- MLOps security
- Apache Airflow
- Kubernetes integration for MLOps
- Amazon SageMaker for MLOps
- Lab: Bring your own algorithm to an MLOps pipeline
- Demonstration: Amazon SageMaker
- Intro to build, train, and evaluate machine learning models
- Lab: Code and serve your ML model with AWS CodeBuild
- Activity: MLOps Action Plan Workbook
- Introduction to deployment operations
- Model packaging
- Inference
- Lab: Deploy your model to production
- SageMaker production variants
- Deploying to the edge
- Lab: Conduct A/B testing
- Lab: Troubleshoot your pipeline
- The importance of monitoring
- Monitoring by design
- Lab: Monitor your ML model
- Human-in-the-loop
- Amazon SageMaker Model Monitor
- Demonstration: Amazon SageMaker Pipelines, Model Monitor, model registry, and Feature Store
- Solving the Problem(s)
- Wrap-up
Contact Learning Advisor
Meet the instructor and learn about the course content and teaching style.- Make informed decisions about whether to enroll in the course or not.
- Get a perspective with a glimpse of what the learning process entails.
Description
Target Audience:
- Machine learning engineers
- Data scientists
- Developers interested in machine learning
- Technical managers looking to implement machine learning in their organization
Prerequisites:
- Basic knowledge of machine learning concepts and Python programming
- Familiarity with AWS services is recommended but not required
Benefits of the course:
- Hands-on experience with cutting-edge MLOps technologies on AWS
- Learn from industry experts with real-world experience
- Gain the skills needed to build and deploy machine learning models in production
- Boost your career prospects with an in-demand skill set
Exam details to pass the course:
- There is no exam required to pass the course.
- Participants will receive a certificate of completion upon finishing the course.
Certification path:
- Participants can pursue the AWS Certified Machine Learning – Specialty certification after completing this course.
Career options after doing the course:
- Machine learning engineer
- Data scientist
- MLOps engineer
- Technical manager in machine learning projects
Why should you take this course from Skillzcafe:
Why should you take this course from Skillzcafe:
Experienced and certified trainers with a proven track record of success- Comprehensive curriculum covering all aspects of MLOps on AWS
- Hands-on experience with real-world use cases and projects
- Access to our online learning platform with 24/7 support
FAQs
MLOps is a set of practices that combines machine learning and DevOps to improve the efficiency and effectiveness of machine learning workflows.
Basic knowledge of machine learning concepts and Python programming is recommended for this course.
Familiarity with AWS services is recommended, but not required. The course provides an overview of AWS services and hands-on experience with these services.
The duration of the course is 3 days.
Yes, you will receive a certificate of completion upon finishing the course. This certificate is recognized by industry leaders and can be added to your resume or LinkedIn profile.
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