Aws Certified Machine Learning Engineer Associate - Complete

Master AWS Machine Learning with hands-on lectures covering SageMaker, data prep, deployment pipelines, and monitoring.

What you'll learn

Master key AWS ML services including SageMaker, Bedrock, and Comprehend through hands-on demonstrations and practical implementation.

Design, deploy, and monitor machine learning pipelines on AWS using services like CloudWatch, CloudTrail, and SageMaker Model Monitor.

Implement data preparation workflows using AWS analytics services including Glue, EMR, and Athena for effective ML model development.

Develop secure and cost-effective ML solutions by implementing best practices in IAM policies, encryption, and resource optimization.

Requirements

Basic cloud computing knowledge is helpful but not required. This course is designed for IT professionals with some programming experience in Python, Java, or similar languages. Familiarity with data concepts and AWS fundamentals is beneficial, but comprehensive hands-on demonstrations will guide you through each service. You'll need an AWS account (free tier is sufficient) and a computer with internet access to follow along with the practical exercises.

Description

Are you ready to master AWS Machine Learning and earn your certification? This comprehensive course prepares you for the AWS Certified Machine Learning Engineer Associate exam while building practical, hands-on skills you can apply immediately.What This Course OffersThrough a perfect balance of theory and practice, you'll master all services covered in the MLA-C01 exam. Each section includes conceptual lectures followed by hands-on demonstrations where you'll implement what you've learned in real AWS environments.Course HighlightsComplete Coverage: Learn all essential AWS services required for the certification, including Amazon SageMaker, Bedrock, Comprehend, Rekognition, and many more.Hands-On Learning: Follow along with practical demonstrations for each key service, reinforcing theoretical concepts with real implementation experience.Data Preparation Mastery: Develop expertise in AWS analytics services like Glue, EMR, Athena, and Kinesis to prepare data for machine learning workflows.Deployment & Orchestration: Learn to deploy ML models using various AWS services and build automated CI/CD pipelines for ML workflows.Monitoring & Security: Implement best practices for monitoring ML solutions, optimizing costs, and securing ML infrastructure using IAM, KMS, and other security services.Beyond CertificationWhile this course thoroughly prepares you for the AWS Certified Machine Learning Engineer Associate exam, it goes beyond theoretical knowledge. You'll develop practical skills in designing, implementing, and maintaining ML solutions on AWS that you can apply in real-world projects.Whether you're new to machine learning on AWS or looking to formalize your knowledge with certification, this course provides everything you need to succeed as an AWS Machine Learning Engineer.Join now and take the next step in your cloud and machine learning career!

Overview

Section 1: Introduction

Lecture 1 About The Instructor

Section 2: Analytics

Lecture 2 Amazon Athena

Lecture 3 Amazon Athena - Hands-On Demo

Lecture 4 Amazon Data Firehose

Lecture 5 Amazon EMR

Lecture 6 Amazon EMR - Hands-On Demo

Lecture 7 AWS Glue

Lecture 8 AWS Glue - Hands-On Demo

Lecture 9 Amazon Kinesis

Lecture 10 Amazon Kinesis - Hands-On Demo

Lecture 11 AWS Lake Formation

Lecture 12 AWS Lake Formation - Hands-On Demo

Lecture 13 Amazon Managed Service for Apache Flink

Lecture 14 Amazon OpenSearch Service

Lecture 15 Amazon OpenSearch Service - Hands-On Demo

Lecture 16 Amazon QuickSight

Lecture 17 Amazon QuickSight - Hands-On Demo

Lecture 18 Amazon Redshift

Lecture 19 Amazon Redshift- Hands-On Demo

Section 3: Application Integration

Lecture 20 Amazon EventBridge

Lecture 21 Amazon EventBridge - Hands-On Demo

Lecture 22 Amazon Simple Notification Service (Amazon SNS)

Lecture 23 Amazon Simple Notification Service (Amazon SNS) - Hands-On Demo

Lecture 24 Amazon Simple Queue Service (Amazon SQS)

Lecture 25 Amazon Simple Queue Service (Amazon SQS) - Hands-On Demo

Lecture 26 AWS Step Functions

Lecture 27 AWS Step Functions - Hands-On Demo

Section 4: Cloud Financial Management

Lecture 28 AWS Billing and Cost Management

Lecture 29 AWS Budgets

Lecture 30 AWS Budgets - Hands-On Demo

Lecture 31 AWS Cost Explorer

Lecture 32 AWS Cost Explorer - Hands-On Demo

Section 5: Compute

Lecture 33 AWS Batch

Lecture 34 AWS Batch - Hands-On Demo

Lecture 35 Amazon EC2

Lecture 36 Amazon EC2 - Hands-On Demo

Lecture 37 AWS Lambda

Lecture 38 AWS Lambda - Hands-On Demo

Lecture 39 AWS Serverless Application Repository

Section 6: Containers

Lecture 40 Amazon Elastic Container Registry (Amazon ECR)

Lecture 41 Amazon Elastic Container Registry (Amazon ECR) - Hands-On Demo

Lecture 42 Amazon Elastic Container Service (Amazon ECS)

Lecture 43 Amazon Elastic Container Service (Amazon ECS) - Hands-On Demo

Lecture 44 Amazon Elastic Kubernetes Service (Amazon EKS)

Lecture 45 Amazon Elastic Kubernetes Service (Amazon EKS) - Hands-On Demo

Section 7: Database

Lecture 46 Amazon DocumentDB (with MongoDB compatibility)

Lecture 47 Amazon DynamoDB

Lecture 48 Amazon DynamoDB - Hands-On Demo

Lecture 49 Amazon ElastiCache

Lecture 50 Amazon Neptune

Lecture 51 Amazon RDS

Lecture 52 Amazon RDS - Hands-On Demo

Section 8: Developer Tools

Lecture 53 AWS Cloud Development Kit (AWS CDK)

Lecture 54 AWS CodeArtifact

Lecture 55 AWS CodeBuild

Lecture 56 AWS CodeDeploy

Lecture 57 AWS CodePipeline

Lecture 58 AWS X-Ray

Section 9: Machine Learning

Lecture 59 Amazon Bedrock

Lecture 60 Amazon CodeGuru

Lecture 61 Amazon Comprehend

Lecture 62 Amazon Fraud Detector

Lecture 63 Amazon Kendra

Lecture 64 Amazon Lex

Lecture 65 Amazon Personalize

Lecture 66 Amazon Polly

Lecture 67 Amazon Rekognition

Lecture 68 Amazon SageMaker

Lecture 69 Amazon Textract

Lecture 70 Amazon Transcribe

Lecture 71 Amazon Translate

Section 10: Management and Governance

Lecture 72 AWS Auto Scaling

Lecture 73 AWS CloudFormation

Lecture 74 AWS CloudFormation - Hands-On Demo

Lecture 75 AWS CloudTrail

Lecture 76 AWS CloudTrail - Hands-On Demo

Lecture 77 Amazon CloudWatch

Lecture 78 Amazon CloudWatch - Hands-On Demo

Lecture 79 Amazon CloudWatch Logs

Lecture 80 AWS Compute Optimizer

Lecture 81 AWS Config

Lecture 82 AWS Config - Hands-On Demo

Lecture 83 AWS Config - Hands-On Demo - Clean Up

Lecture 84 AWS Organizations

Lecture 85 AWS Organizations - Hands-On Demo

Lecture 86 AWS Service Catalog

Lecture 87 AWS Systems Manager

Lecture 88 AWS Systems Manager - Hands-On Demo

Lecture 89 AWS Trusted Advisor

Lecture 90 AWS Trusted Advisor - Hands-On Demo

Section 11: Media

Lecture 91 Amazon Kinesis Video Streams

Section 12: Migration and Transfer

Lecture 92 AWS DataSync

Section 13: Networking and Content Delivery

Lecture 93 Amazon API Gateway

Lecture 94 Amazon API Gateway - Hands-On Demo

Lecture 95 Amazon CloudFront

Lecture 96 Amazon CloudFront - Hands-On Demo

Lecture 97 AWS Direct Connect

Lecture 98 Amazon VPC

Lecture 99 Amazon VPC - Part 2

Lecture 100 Amazon VPC - Hands-On Demo

Section 14: Security, Identity, and Compliance

Lecture 101 AWS Identity and Access Management (IAM)

Lecture 102 AWS Identity and Access Management (IAM) - Hands-On Demo

Lecture 103 AWS Key Management Service (AWS KMS)

Lecture 104 AWS Key Management Service (AWS KMS) - Hands-On Demo

Lecture 105 Amazon Macie

Lecture 106 AWS Secrets Manager

Lecture 107 AWS Secrets Manager - Hands-On Demo

Section 15: Storage

Lecture 108 Amazon Elastic Block Store (Amazon EBS)

Lecture 109 Amazon Elastic Block Store (EBS) - Hands-On Demo

Lecture 110 Amazon Elastic File System (Amazon EFS)

Lecture 111 Amazon Elastic File System (EFS) - Hands-On Demo

Lecture 112 Amazon FSx

Lecture 113 Amazon S3 - Part 1

Lecture 114 Amazon S3 - Part 2

Lecture 115 Amazon S3 - Part 3

Lecture 116 Amazon S3 - Part 4

Lecture 117 Amazon S3 - Hands-On Demo

Lecture 118 Amazon S3 Glacier

Lecture 119 AWS Storage Gateway

This course is ideal for IT professionals, software developers, data engineers, and cloud practitioners preparing for the AWS Certified Machine Learning Engineer Associate exam. It's designed for those looking to expand their skills into machine learning on AWS, whether they're currently working with AWS services or planning to transition into machine learning roles. The comprehensive curriculum benefits both certification candidates and professionals seeking to implement practical ML solutions using AWS services. With both theoretical lectures and hands-on demonstrations, this course provides value to learners at various stages in their ML journey, from those with basic AWS knowledge to experienced developers wanting to specialize in AWS machine learning implementation.