09-05-2024, 10:32 AM
![[Image: 3689b91c3a8e78d126a9efd78faca497.jpg]](https://i123.fastpic.org/big/2024/0905/97/3689b91c3a8e78d126a9efd78faca497.jpg)
Mlops With Aws - Bootcamp - Zero To Hero Series
Last updated 8/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English (US) | Size: 13.05 GB | Duration: 34h 1m
Empower Your MLOps Journey: AWS AI/ML Mastery - From Notebook to Production Operation with Expert Guidance - MLOps 2024
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
Requirements
Basic knowledge of AWS
Account with AWS for practical Hand-On
Basic knowledge of Machine Learning & Deep Learning
Description
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
esign, 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 MasterySection 1: Introduction to the AWSMLOPS Course and InstructorGet acquainted with the course objectives and the experienced instructor leading the way.Section 2: Understanding MLOpsDelve into the core concepts of MLOps, understanding its significance and application.Section 3: DevOps Principles for Data ScientistsExplore the principles of DevOps tailored for data scientists, bridging the gap between development and operations.Section 4: Getting Started with AWSAcquaint yourself with the AWS platform, laying the foundation for subsequent sections.Sections 5-16: In-Depth ExplorationA 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 ApplicationsTools and Technologies Coveredata Ingestion and CollectionData Processing and ETL (Extract, Transform, Load)Data Analysis and VisualizationModel Training and Deployment/InferenceOperational Aspects of Machine LearningAWS Machine Learning Application ServicesNotebooks and Integrated Development Environments (IDEs)Version Control with AWS CodeCommitAmazon Athena, AWS Batch, Amazon EC2Amazon Elastic Container Registry (Amazon ECR), AWS GlueAmazon CloudWatch, AWS LambdaAmazon S3 for Storage and ScalabilityAccess 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 TodayWhy 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!
Who this course is for:
Anyone preparing for Data Science , Machine Learning & Deep Learning Interviews,Anyone interested in learning how Machine Learning is implemented on Large scale data,Anyone interested in AWS cloud-based machine learning and data science,Anyone looking to learn the best practices to deploy the Machine Learning Models on Cloud,Anyone looking to learn the best practices to Operationalize the Machine Learning Models
For More Courses Visit & Bookmark Your Preferred Language Blog
From Here: - - - - - - - -
![[Image: ZrNfksbq_o.jpg]](https://images2.imgbox.com/c4/c0/ZrNfksbq_o.jpg)
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
Requirements
Basic knowledge of AWS
Account with AWS for practical Hand-On
Basic knowledge of Machine Learning & Deep Learning
Description
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
esign, 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 MasterySection 1: Introduction to the AWSMLOPS Course and InstructorGet acquainted with the course objectives and the experienced instructor leading the way.Section 2: Understanding MLOpsDelve into the core concepts of MLOps, understanding its significance and application.Section 3: DevOps Principles for Data ScientistsExplore the principles of DevOps tailored for data scientists, bridging the gap between development and operations.Section 4: Getting Started with AWSAcquaint yourself with the AWS platform, laying the foundation for subsequent sections.Sections 5-16: In-Depth ExplorationA 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 ApplicationsTools and Technologies Coveredata Ingestion and CollectionData Processing and ETL (Extract, Transform, Load)Data Analysis and VisualizationModel Training and Deployment/InferenceOperational Aspects of Machine LearningAWS Machine Learning Application ServicesNotebooks and Integrated Development Environments (IDEs)Version Control with AWS CodeCommitAmazon Athena, AWS Batch, Amazon EC2Amazon Elastic Container Registry (Amazon ECR), AWS GlueAmazon CloudWatch, AWS LambdaAmazon S3 for Storage and ScalabilityAccess 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 TodayWhy 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! Who this course is for:
Anyone preparing for Data Science , Machine Learning & Deep Learning Interviews,Anyone interested in learning how Machine Learning is implemented on Large scale data,Anyone interested in AWS cloud-based machine learning and data science,Anyone looking to learn the best practices to deploy the Machine Learning Models on Cloud,Anyone looking to learn the best practices to Operationalize the Machine Learning Models
For More Courses Visit & Bookmark Your Preferred Language Blog
From Here: - - - - - - - -
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