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Aws Certified Machine Learning Engineer - Associate Mla-C01
Published 9/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 9.75 GB | Duration: 25h 51m
The ONLY course you need to PASS the AWS Certified Machine Learning Engineer Exam | MLA-C01 | Incl. FULL Practice Exam!
What you'll learn
PASS the AWS Certified Machine Learning Engineer Associate Exam (MLA-C01)
Full Practice Exam incl. Full Explanations to ACE the exam
All Slides available as downloadable PDFs
All Topics Covered & 100% up-to-date
Hands-on Demos with Real-World Scenarios
Start your Machine Learning Career
Build, Train & Deploy Machine Learning Models in Amazon SageMaker
Data Ingestion and Preprocessing with SageMaker Data Wrangler
Full Machine Learning Pipelines with SageMaker & Much More
Master the Full Machine Learning Lifecycle with Real-World Skills
Requirements
No previous experience with AWS or Machine Learning is needed!
Description
The ONLY course you need to prepare and PASS the AWS Certified Machine Learning Engineer - Associate exam (MLA-C01) and become an AWS Certified Machine Learning Engineer - Associate!Make your exam preparation and learning Machine Learning on AWS fun, easy, and highly effective with real-life hands-on projects, quizzes, and a full practice exam!This course teaches you every single topic you need to master the exam with ease.Why is this the ONLY course you need to pass the AWS Certified Machine Learning Engineer exam?Every single topic is covered in depth100% up-to-date!Hands-On & PracticalFull practice exam including all explanationsPractical & Real-World SkillsTips for successThis course guides you step-by-step to prepare in the best possible way for the examDon't waste your time but focuses on what really matters to master the exam!This course guides you step-by-step to prepare in the best possible way for the exam and start your successful career in machine learning!Your InstructorHi, my name is Nikolai, and I am AWS Certified and I teach AWS and data analytics in over 200 countries. My mission with this course is to take the stress out of your exam prep, make it fun but very effective to maximize your preparation time. I want to make sure you have the best chances of succeeding and moving your career forward with the AWS Machine Learning Engineer certification in your professional journey.Enroll Now and Get:Lifetime Access including all future updatesHigh quality video contentAll slides & project files as downloadable resourcesFull practice exam with explanationsTipps for success & expert-level support30-day money-back guarantee (no-questions-asked!)Become an Expert & Learn the Full Machine Learning Lifecycle in AWS:PASS the AWS Certified Machine Learning Engineer examMaster Machine Learning on AWS and become an expertBuild, train, and deploy machine learning models with SageMakerOrchestrate ML workflows with SageMaker PipelinesPerform data ingestion and transformation with SageMaker Data Wrangler and AWS GlueUse SageMaker Feature Store for feature engineeringDeploy models using real-time, batch, and serverless inferenceMonitor models in production with SageMaker Model MonitorDebug and optimize models with SageMaker Debugger and ProfilerImplement responsible AI practices with SageMaker ClarifyUnderstand AWS storage and data processing services relevant to MLSecure your ML workflows with IAM, KMS, and VPCsImplement CI/CD pipelines for ML using SageMaker and AWS CodePipelineOptimize costs and monitor ML workloads with CloudWatch and AWS Cost Management toolsAnd much more!Whether you're new to machine learning or looking to expand your AWS expertise, this course offers everything you need-practical labs, a full practice exam, and up-to-date content that covers every aspect of Machine Learning on AWS.Take this chance today - this can be your first step into a successful machine learning engineering career!Looking forward to seeing you inside the course!
Overview
Section 1: Introduction
Lecture 1 Welcome!
Lecture 2 About the exam & this course
Lecture 3 Important tips for this course
Lecture 4 All Slides
Section 2: SageMaker: Basics & Setup
Lecture 5 AWS Free Tier Account ML
Lecture 6 SageMaker Overview
Lecture 7 SageMaker Notebooks
Lecture 8 Setting Up SageMaker Notebook Instance
Lecture 9 Basic Operations in SageMaker Notebook Instance
Lecture 10 SageMaker Studio Setting Up Domain & Users
Lecture 11 SageMaker Studio Overview
Lecture 12 AWS Budgets Machine Learning
Section 3: SageMaker: Data Ingestion & Feature Engineering
Lecture 13 Data Preparation with Data Wrangler
Lecture 14 Import data using Data Wrangler
Lecture 15 Data Wrangler - Get Insights
Lecture 16 Data Wrangler Transform Data
Lecture 17 Export Data in Data Wrangler
Lecture 18 Stop Running Instances
Lecture 19 Understanding Feature Engineering
Lecture 20 SageMaker Feature Store
Lecture 21 Feature Store - Creating Features & Feature Group
Lecture 22 SageMaker Notebooks- Setting up Features
Lecture 23 SageMaker Ground Truth
Lecture 24 Create Labeling Jobs in Groud Truth
Lecture 25 Setting up Groud Truth Workforce
Lecture 26 Ground Truth Plus
Section 4: SageMaker: Training & Hyperparameter Tuning
Lecture 27 Training with Built-in Algorithms
Lecture 28 SageMaker JumpStart
Lecture 29 Deploy a Model Using JumpStart
Lecture 30 Training Models - Potential Paths
Lecture 31 Prepare The Training Of The Model
Lecture 32 Train Model
Lecture 33 Reviewing the Trained Model
Lecture 34 Model Tuning & Hyperparameters
Lecture 35 Hyperparamter Optimization Techniques
Lecture 36 Hyperparameter Tuning in Notebooks
Lecture 37 Hyperparameter Tuning in the UI
Lecture 38 SageMaker Canvas
Lecture 39 SageMaker Canvas Using AutoML
Lecture 40 SageMaker Canvas Predict & Deploy
Lecture 41 Custom Training Script
Lecture 42 Custom Docker Containers
Lecture 43 Distributed Training
Section 5: SageMaker: Experiment Tracking & Debugging
Lecture 44 SageMaker Experiments
Lecture 45 MLflow Setting Up Tracking Server
Lecture 46 MLflow Setup Experiment
Lecture 47 MLflow Track & Record Experiments
Lecture 48 SageMaker Neo
Section 6: SageMaker: Clarify & Responsible AI
Lecture 49 Challenges of Responsible Al
Lecture 50 Strategies Against Bias & Variance
Lecture 51 SageMaker Clarify
Lecture 52 SageMaker Clarify Pre-Training Analysis
Lecture 53 SageMaker Clarify Review Pre-Training Analysis
Lecture 54 SageMaker Clarify Model Bias Analysis
Lecture 55 SageMaker Clarify Explainability Report
Section 7: SageMaker: Debugging & Deployment
Lecture 56 SageMaker Debugger
Lecture 57 SageMaker Debugger (Hands-on)
Lecture 58 Model Deployment Strategies in SageMaker
Lecture 59 Deploy Real-Time Inference Endpoint
Lecture 60 Deploying Endpoint using Model Artifact
Lecture 61 Serverless Inference Endpoint
Lecture 62 Deploy Using Batch Transform
Lecture 63 Deploy as Asynchronous Inference Endpoint
Lecture 64 Multi-Model & Multi-Container Endpoints in SageMaker
Lecture 65 Deploying a Multi-Model Endpoint
Section 8: SageMaker: Monitoring Models
Lecture 66 Monitoring Models
Lecture 67 SageMaker Model Monitor
Lecture 68 Monitoring Data Quality in SageMaker
Lecture 69 Monitor Model Quality with SageMaker
Lecture 70 Model Monitoring Create a Baseline
Lecture 71 SageMaker Monitor Create a Schedule
Section 9: SageMaker: Pipelines & Model Registry
Lecture 72 SageMaker Pipelines
Lecture 73 SageMaker Pipelines (Hands-on)
Lecture 74 Model Registry
Lecture 75 SageMaker Model Registry
Section 10: Machine Learning Concepts
Lecture 76 Understanding Machine Learning Models
Lecture 77 Supervised Learning
Lecture 78 Unsupervised Learning
Lecture 79 Text Analysis Algorithms
Lecture 80 Image Classification
Lecture 81 Reinforcement Learning
Lecture 82 Reinforcement Learning with SageMaker
Lecture 83 Model Evaluation Concepts
Lecture 84 Performance Evaluation Metrics
Lecture 85 Machine Learning Development Lifecycle
Lecture 86 MLOps
Section 11: AWS Machine Learning Services
Lecture 87 What is Amazon Bedrock?
Lecture 88 Amazon Bedrock - Architecture
Lecture 89 Amazon Bedrock - Use Cases
Lecture 90 Hands-on: Exploring Amazon Bedrock
Lecture 91 Hands-on: Installing Visual Studio Code
Lecture 92 Hands-on: Setting up Visual Studio Code
Lecture 93 Hands-on: Invoking Amazon Titan Model
Lecture 94 Hands-on: Image Generation in Bedrock
Lecture 95 Amazon Personalize
Lecture 96 Hands-on: Dataset Group (Amazon Personalize)
Lecture 97 Hands-on: Training Dataset (Amazon Personalize)
Lecture 98 Hands-on: Train Model (Amazon Personalize)
Lecture 99 Hands-on: Make Predictions (Amazon Personalize)
Lecture 100 Amazon Fraud Detector
Lecture 101 Setup & Event Type (Amazon Fraud Detector)
Lecture 102 Build & Train Model (Amazon Fraud Detector)
Lecture 103 Evaluate our Model (Amazon Fraud Detector)
Lecture 104 Create Detector & Make Predictions (Amazon Fraud Detector)
Lecture 105 Cleaning up Resources (Amazon Fraud Detector)
Lecture 106 Amazon Augmented AI
Lecture 107 Amazon Comprehend
Lecture 108 Hands-on: Amazon Comprehend
Lecture 109 Amazon Comprehend Medical Hands on
Lecture 110 Amazon Rekognition
Lecture 111 Hands-on: Amazon Rekognition
Lecture 112 Hands-on: Using Rekognition in Lambda Function
Lecture 113 Amazon Textract
Lecture 114 Hands-on: Amazon Textract
Lecture 115 Amazon Kendra
Lecture 116 Hands-on: Create an Index & Sync (Amazon Kendra)
Lecture 117 Hands-on: Create Experience (Amazon Kendra)
Section 12: Data Ingestion
Lecture 118 AWS S3 - Basics
Lecture 119 Create a Bucket in S3 (Hands-on)
Lecture 120 Uploading files to S3 (Hands-on)
Lecture 121 Streaming vs Batch Ingestion
Lecture 122 AWS Glue
Lecture 123 Setting Up Crawlers (Hands-on)
Section 13: Querying with Athena
Lecture 124 AWS Athena - Overview
Lecture 125 Query data using Athena (Hands-on)
Lecture 126 Federated Queries
Lecture 127 Performance & Cost
Lecture 128 Workgroups
Lecture 129 Workgroups (Hands-on)
Section 14: AWS Data Processing Services
Lecture 130 Glue Costs
Lecture 131 Run Glue ETL Jobs (Hands-on)
Lecture 132 Scheduling Crawlers & ETL Jobs (Hands-on)
Lecture 133 Stateful vs Stateless
Lecture 134 Stateless Data Ingestion in Glue (Hands-on)
Lecture 135 Stateful Ingestion with Bookmarks (Hands-on)
Lecture 136 Glue Transformations (ETL)
Lecture 137 Glue Data Quality (Hands-on)
Lecture 138 Glue Workflows
Lecture 139 Glue Workflows - (Hands-on)
Lecture 140 Glue Job Types
Lecture 141 Glue Job Types (Hands-on)
Lecture 142 Partitioning
Lecture 143 AWS Glue DataBrew
Lecture 144 AWS Glue DataBrew - Transformations
Lecture 145 AWS Glue DataBrew (Hands-On)
Lecture 146 AWS Lambda
Lecture 147 Event-Driven Ingestion with AWS Lambda (Hands-on)
Lecture 148 Lambda Layers
Lecture 149 Replayability
Lecture 150 Amazon Kinesis for Streaming Data
Lecture 151 Amazon Kinesis Data Streams
Lecture 152 Throughput and Latency
Lecture 153 Creating a Data Stream (Hands-on)
Lecture 154 Enhanced Fan-Out for Kinesis Consumers
Lecture 155 Pull and Consume Data From Stream (Hands-on)
Lecture 156 Calling a Lambda Function From Amazon Kinesis (Hands-on)
Lecture 157 Common Issues & Troubleshooting
Lecture 158 Kinesis Firehose
Lecture 159 Creating Data Firehose Stream (Hands-on)
Lecture 160 Data Firehose - Transformations with Lambda (Hands-on)
Lecture 161 Amazon Managed Service for Apache Flink
Lecture 162 Amazon MSK
Lecture 163 MSK Connect & MSK Serverless
Lecture 164 Amazon EMR
Lecture 165 AWS EMR Cluster Types & Storage
Lecture 166 AWS EMR Storage & Scaling
Lecture 167 AWS EMR Deployment Options
Section 15: AWS Storage Solutions
Lecture 168 Importance of Partitioning
Lecture 169 Partitioning with Glue (Hands-on)
Lecture 170 Lifecycle Management & Storage Classes
Lecture 171 Using Lifecycle Rules
Lecture 172 Storage Classes (Hands-on)
Lecture 173 Intelligent Tiering (Hands-on)
Lecture 174 Lifecycle Rules (Hands-on)
Lecture 175 Versioning in S3
Lecture 176 Versioning (Hands-on)
Lecture 177 Replication
Lecture 178 Replication (Hands-on)
Lecture 179 Security in S3
Lecture 180 Security (Hands-on)
Lecture 181 Bucket Policies
Lecture 182 Access Points in S3
Lecture 183 Object Lambda
Lecture 184 S3 Event Notifications
Lecture 185 S3 Event Notifications (Hands-on)
Lecture 186 S3 Select & Glacier Select
Lecture 187 S3 Select (Hands-on)
Lecture 188 Data Mesh
Lecture 189 Data Exchange
Lecture 190 Amazon Elastic Block Store (EBS)
Lecture 191 EBS Provisioning
Lecture 192 EBS Volumes (Hands-on)
Lecture 193 Amazon Elastic File System (EFS)
Section 16: AWS Security and Compliance
Lecture 194 IAM Overview
Lecture 195 IAM Users, Groups & Role
Lecture 196 IAM Policies
Lecture 197 IAM Create User (Hands-on)
Lecture 198 IAM Policies (Hands-on)
Lecture 199 IAM Create Groups & Roles (Hands-on)
Lecture 200 AWS KMS Overview
Lecture 201 AWS KMS Key Management & Pricing
Lecture 202 AWS KMS Cross-Region & Cross-Account
Lecture 203 AWS Macie
Lecture 204 AWS Secrets
Lecture 205 AWS Secrets (Hands-on)
Lecture 206 AWS Shield
Lecture 207 Virtual Private Cloud & Subnets
Lecture 208 Gateways
Lecture 209 VPN & VPC Peering
Lecture 210 Security Groups & NACLs
Lecture 211 Additional VPC features
Lecture 212 AWS CloudTrail
Lecture 213 AWS CloudTrail Lake
Lecture 214 AWS Config
Lecture 215 AWS Config (Hands-on)
Lecture 216 AWS Well-Architected Framework
Lecture 217 AWS Well-Architected Tool
Section 17: AWS Deployment and Orchestration Services
Lecture 218 AWS CloudFormation
Lecture 219 AWS CloudFormation (Hands-on)
Lecture 220 Docker Containers
Lecture 221 Amazon ECS
Lecture 222 Amazon ECS - Launch Types
Lecture 223 Amazon ECS - IAM Roles
Lecture 224 Amazon ECR
Lecture 225 Amazon EKS
Section 18: AWS Monitoring and Cost Management Tools
Lecture 226 Amazon CloudWatch Overview
Lecture 227 Amazon CloudWatch Metrics (Hands-on)
Lecture 228 Amazon CloudWatch Metrics Stream
Lecture 229 Amazon CloudWatch Alarms
Lecture 230 CloudWatch Alarms (Hands-on)
Lecture 231 Amazon CloudWatch Logs
Lecture 232 CloudWatch Logs (Hands-on)
Lecture 233 Amazon CloudWatch Log Filtering & Subscription
Lecture 234 Amazon CloudWatch Logs Agent
Section 19: AWS AI Services
Lecture 235 What is Amazon Q Business
Lecture 236 Hands-on: Create Amazon Q Business Application
Lecture 237 Hands-on: Assign Users & Test Application
Lecture 238 Hands-on: Using Global Controls
Lecture 239 Hands-on: Blocking Words
Lecture 240 Hands-on: Topic Controls
Lecture 241 Amazon Transcribe
Lecture 242 Hands-on: Amazon Transcribe
Lecture 243 Amazon Polly
Lecture 244 Hands-on: Pricing & Models (Amazon Polly)
Lecture 245 Hands-on: Text-to-Speech (Amazon Polly)
Lecture 246 Hands-on: SSML to modify speech output (Amazon Polly)
Lecture 247 Hands-on: Real-time translation (Amazon Translate)
Lecture 248 Hands-on: Batch job translation (Amazon Translate)
Section 20: Practice Exam, Exam Tips & Scheduling
Lecture 249 Exam Signup & Get 30min more time!
Lecture 250 Final Exam Tips
Aspiring Machine Learning Engineers looking to get certified and kickstart their ML careers,Data Scientists, Data Engineers, Developers, and IT Professionals,Professionals seeking to expand their knowledge of Machine Learning on AWS
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