Curriculum For This Course

Introduction

1Lectures

Time 00:07:46

SageMaker: Basics & Setup

8Lectures

Time 01:00:32

SageMaker: Data Preparation with Data Wrangler

14Lectures

Time 01:38:43

SageMwker: Training & Hyperparameter Tuning

17Lectures

Time 01:52:33

SageMaker: Experiment Tracking

5Lectures

Time 00:33:36

Clarify & Responsible AI

7Lectures

Time 00:49:59

SageMaker: Debugging & Deployment

12Lectures

Time 01:13:41

SageMaker Monitoring Models

6Lectures

Time 00:36:44

SageMaker: Pipelines & Model Registry

5Lectures

Time 00:27:31

Machine Learning Concepts

11Lectures

Time 01:09:38

AWS Machine Learning Services

28Lectures

Time 03:04:45

Data Ingestion

6Lectures

Time 00:36:02

Querying with Athena

6Lectures

Time 00:27:52

AWS Data Processing Services

37Lectures

Time 04:05:25

AWS Storage Solutions

24Lectures

Time 02:21:51

AWS Security and Compliance

24Lectures

Time 01:53:52

AWS Deployment and Orchestration Services

8Lectures

Time 00:51:03

AWS Monitoring and Cost Management Tools

9Lectures

Time 00:48:09

AWS AI Services

14Lectures

Time 01:37:48

Practice Exam, Exam Tips & Scheduling

2Lectures

Time 00:15:26

Introduction
	1. About the exam & this course	7:46

SageMaker: Basics & Setup
	1. AWS Free Tier Account	6:18
	2. SageMaker Overview	8:17
	3. SageMaker Notebooks	6:14
	4. Setting Up SageMaker Notebook Instance	6:58
	5. Basic Operations in SageMaker Notebook Instance	9:09
	6. SageMaker Studio Setting Up Domain & Users	8:08
	7. SageMaker Studio Overview	8:57
	8. AWS Budgets	6:31

SageMaker: Data Preparation with Data Wrangler
	1. Data Preparation with Data Wrangler	4:38
	2. Import data using Data Wrangler	6:51
	3. Data Wrangler - Get Insights	5:56
	4. Data Wrangler Transform Data	9:54
	5. Export Data in Data Wrangler	6:48
	6. Stop Running Instances	2:08
	7. Understanding Feature Engineering	10:22
	8. SageMaker Feature Store	5:24
	9. Feature Store - Creating Features & Feature Group	9:58
	10. SageMaker Notebooks- Setting up Features	8:59
	11. SageMaker Ground Truth	6:25
	12. Setting up Groud Truth Workforce	5:25
	13. Create Labeling Jobs in Groud Truth	14:25
	14. Ground Truth Plus	1:30

SageMwker: Training & Hyperparameter Tuning
	1. Training with Built-in Algorithms	3:08
	2. SageMaker JumpStart	6:17
	3. Deploy a Model Using JumpStart	11:03
	4. Training Models - Potential Paths	9:00
	5. Prepare The Training Of The Model	10:53
	6. Train Model	7:10
	7. Reviewing the Trained Model	2:26
	8. Model Tuning & Hyperparameters	4:38
	9. Hyperparamter Optimization Techniques	5:07
	10. Hyperparameter Tuning in Notebooks	8:26
	11. Hyperparameter Tuning in the UI	6:03
	12. SageMaker Canvas	6:54
	13. SageMaker Canvas Using AutoML	8:00
	14. SageMaker Canvas Predict & Deploy	5:41
	15. Custom Training Script	6:49
	16. Custom Docker Containers	4:07
	17. Distributed Training	6:51

SageMaker: Experiment Tracking
	1. SageMaker Experiments	7:55
	2. MLflow Setting Up Tracking Server	7:55
	3. MLflow Setup Experiment	4:58
	4. MLflow Track & Record Experiments	11:48
	5. Delete Tracking Server	1:00

Clarify & Responsible AI
	1. Challenges of Responsible Al	4:13
	2. Strategies Against Bias & Variance	3:54
	3. SageMaker Clarify	6:23
	4. SageMaker Clarify Pre-Training Analysis	10:12
	5. SageMaker Clarify Review Pre-Training Analysis	6:45
	6. SageMaker Clarify Model Bias Analysis	9:25
	7. SageMaker Clarify Explainability Report	9:07

SageMaker: Debugging & Deployment
	1. SageMaker Debugger	4:13
	2. SageMaker Debugger (Hands-on)	15:22
	3. SageMaker Profiling	6:19
	4. Model Deployment Strategies in SageMaker	5:28
	5. Deploy Real-Time Inference Endpoint	6:42
	6. Deploying Endpoint using Model Artifact	3:20
	7. Serverless Inference Endpoint	2:26
	8. Deploy Using Batch Transform	5:24
	9. Deploy as Asynchronous Inference Endpoint	7:30
	10. Multi-Model & Multi-Container Endpoints in SageMaker	4:30
	11. Deploying a Multi-Model Endpoint	6:53
	12. SageMaker Neo	5:34

SageMaker Monitoring Models
	1. Monitoring Models	4:17
	2. SageMaker Model Monitor	2:50
	3. Monitoring Data Quality in SageMaker	5:58
	4. Monitor Model Quality with SageMaker	5:10
	5. Model Monitoring Create a Baseline	10:43
	6. SageMaker Monitor Create a Schedule	7:46

SageMaker: Pipelines & Model Registry
	1. SageMaker Pipelines	4:58
	2. SageMaker Pipelines (Hands-on)	11:04
	3. Model Registry	4:40
	4. SageMaker Model Registry	4:00
	5. Cleaning Up Resources	2:49

Machine Learning Concepts
	1. Understanding Machine Learning Models	7:48
	2. Supervised Learning	9:05
	3. Unsupervised Learning	6:17
	4. Text Analysis Algorithms	4:46
	5. Image Classification	5:31
	6. Reinforcement Learning	5:08
	7. Reinforcement Learning with SageMaker	3:46
	8. Model Evaluation Concepts	4:31
	9. Performance Evaluation Metrics	6:24
	10. Machine Learning Development Lifecycle	7:57
	11. MLOps	8:25

AWS Machine Learning Services
	1. What is Amazon Bedrock?	8:16
	2. Amazon Bedrock - Architecture	4:05
	3. Amazon Bedrock - Use Cases	1:49
	4. Hands-on: Exploring Amazon Bedrock	8:53
	5. Hands-on: Installing Visual Studio Code	1:40
	6. Amazon Personalize	2:28
	7. Hands-on: Dataset Group (Amazon Personalize)	10:51
	8. Hands-on: Training Dataset (Amazon Personalize)	3:08
	9. Hands-on: Train Model (Amazon Personalize)	6:08
	10. Hands-on: Make Predictions (Amazon Personalize)	6:59
	11. Amazon Fraud Detector	6:50
	12. Setup & Event Type (Amazon Fraud Detector)	11:51
	13. Build & Train Model (Amazon Fraud Detector)	5:23
	14. Evaluate our Model (Amazon Fraud Detector)	9:07
	15. Create Detector & Make Predictions (Amazon Fraud Detector)	10:03
	16. Cleaning up Resources (Amazon Fraud Detector)	6:52
	17. Amazon Augmented AI	4:12
	18. Amazon Comprehend	7:17
	19. Hands-on: Amazon Comprehend	6:42
	20. Amazon Comprehend Medical Hands on	5:17
	21. Amazon Rekognition	3:06
	22. Hands-on: Amazon Rekognition	5:10
	23. Hands-on: Using Rekognition in Lambda Function	9:38
	24. Amazon Textract	6:35
	25. Hands-on: Amazon Textract	7:58
	26. Amazon Kendra	6:27
	27. Hands-on: Create an Index & Sync (Amazon Kendra)	9:27
	28. Hands-on: Create Experience (Amazon Kendra)	8:33

Data Ingestion
	1. AWS S3 - Basics	8:44
	2. Create a Bucket in S3 (Hands-on)	4:19
	3. Uploading files to S3 (Hands-on)	2:10
	4. Streaming vs Batch Ingestion	2:56
	5. AWS Glue	6:46
	6. Setting Up Crawlers (Hands-on)	11:07

Querying with Athena
	1. AWS Athena - Overview	4:20
	2. Query data using Athena (Hands-on)	5:16
	3. Federated Queries	2:18
	4. Performance & Cost	10:05
	5. Workgroups	3:04
	6. Workgroups (Hands-on)	2:49

AWS Data Processing Services
	1. Glue Costs	7:34
	2. Run Glue ETL Jobs (Hands-on)	13:19
	3. Scheduling Crawlers & ETL Jobs (Hands-on)	3:36
	4. Stateful vs Stateless	5:10
	5. Stateless Data Ingestion in Glue (Hands-on)	3:40
	6. Stateful Ingestion with Bookmarks (Hands-on)	5:03
	7. Glue Transformations (ETL)	5:09
	8. Glue Data Quality (Hands-on)	5:45
	9. Glue Workflows	4:33
	10. Glue Workflows - (Hands-on)	7:33
	11. Glue Job Types	6:43
	12. Glue Job Types (Hands-on)	2:32
	13. Partitioning	2:55
	14. AWS Glue DataBrew	6:16
	15. AWS Glue DataBrew - Transformations	7:43
	16. AWS Glue DataBrew (Hands-On)	10:09
	17. AWS Lambda	7:07
	18. Event-Driven Ingestion with AWS Lambda (Hands-on)	10:07
	19. Lambda Layers	4:13
	20. Reability	5:57
	21. Amazon Kinesis for Streaming Data	3:34
	22. Amazon Kinesis Data Streams	9:57
	23. Throughput and Latency	4:20
	24. Creating a Data Stream (Hands-on)	5:05
	25. Enhanced Fan-Out for Kinesis Consumers	5:25
	26. Calling a Lambda Function From Amazon Kinesis (Hands-on)	7:59
	27. Common Issues & Troubleshooting	10:53
	28. Kinesis Firehose	12:32
	29. Creating Data Firehose Stream (Hands-on)	7:02
	30. Data Firehose - Transformations with Lambda (Hands-on)	7:43
	31. Amazon Managed Service for Apache Flink	8:31
	32. Amazon MSK	9:07
	33. MSK Connect & MSK Serverless	2:49
	34. Amazon EMR	12:11
	35. AWS EMR Cluster Types & Storage	5:54
	36. AWS EMR Storage & Scaling	3:47
	37. AWS EMR Deployment Options	3:32

AWS Storage Solutions
	1. Importance of Partitioning	3:06
	2. Partitioning with Glue (Hands-on)	11:42
	3. Lifecycle Management & Storage Classes	10:18
	4. Using Lifecycle Rules	1:37
	5. Storage Classes (Hands-on)	5:02
	6. Intelligent Tiering (Hands-on)	4:13
	7. Lifecycle Rules (Hands-on)	4:39
	8. Versioning in S3	5:56
	9. Versioning (Hands-on)	10:08
	10. Replication	6:36
	11. Replication (Hands-on)	6:38
	12. Security in S3	6:27
	13. Security (Hands-on)	4:11
	14. Bucket Policies	2:26
	15. Access Points in S3	2:31
	16. Object Lambda	3:29
	17. S3 Event Notifications	4:48
	18. S3 Event Notifications (Hands-on)	8:44
	19. Data Mesh	3:50
	20. Data Exchange	2:33
	21. Amazon Elastic Block Store (EBS)	6:41
	22. EBS Provisioning	9:24
	23. EBS Volumes (Hands-on)	9:01
	24. Amazon Elastic File System (EFS)	7:51

AWS Security and Compliance
	1. IAM Overview	2:30
	2. IAM Users, Groups & Role	5:11
	3. IAM Policies	8:30
	4. IAM Create User (Hands-on)	4:25
	5. IAM Policies (Hands-on)	6:00
	6. IAM Create Groups & Roles (Hands-on)	5:14
	7. AWS KMS Overview	8:54
	8. AWS KMS Key Management & Pricing	4:25
	9. AWS KMS Cross-Region & Cross-Account	8:00
	10. AWS Macie	2:45
	11. AWS Secrets	5:36
	12. AWS Secrets (Hands-on)	5:20
	13. AWS Shield	3:12
	14. Virtual Private Cloud & Subnets	2:58
	15. Gateways	2:25
	16. VPN & VPC Peering	2:32
	17. Security Groups & NACLs	1:19
	18. Additional VPC features	1:22
	19. AWS CloudTrail	8:09
	20. AWS CloudTrail Lake	1:41
	21. AWS Config	6:25
	22. AWS Config (Hands-on)	7:19
	23. AWS Well-Architected Framework	4:53
	24. AWS Well-Architected Tool	4:47

AWS Deployment and Orchestration Services
	1. AWS CloudFormation	5:11
	2. AWS CloudFormation (Hands-on)	8:37
	3. Docker Containers	8:37
	4. Amazon ECS	5:39
	5. Amazon ECS - Launch Types	8:40
	6. Amazon ECS - IAM Roles	1:59
	7. Amazon ECR	4:46
	8. Amazon EKS	7:34

AWS Monitoring and Cost Management Tools
	1. Amazon CloudWatch Overview	5:32
	2. Amazon CloudWatch Metrics (Hands-on)	6:22
	3. Amazon CloudWatch Metrics Stream	2:36
	4. Amazon CloudWatch Alarms	4:51
	5. CloudWatch Alarms (Hands-on)	9:19
	6. Amazon CloudWatch Logs	3:31
	7. CloudWatch Logs (Hands-on)	9:30
	8. Amazon CloudWatch Log Filtering & Subscription	4:13
	9. Amazon CloudWatch Logs Agent	2:15

AWS AI Services
	1. What is Amazon Q Business	8:28
	2. Hands-on: Create Amazon Q Business Application	14:06
	3. Hands-on: Assign Users & Test Application	7:40
	4. Hands-on: Using Global Controls	6:24
	5. Hands-on: Blocking Words	2:39
	6. Hands-on: Topic Controls	6:44
	7. Amazon Transcribe	8:11
	8. Hands-on: Amazon Transcribe	11:16
	9. Amazon Polly	3:12
	10. Hands-on: Pricing & Models (Amazon Polly)	5:09
	11. Hands-on: Text-to-Speech (Amazon Polly)	4:01
	12. Hands-on: SSML to modify speech output (Amazon Polly)	5:15
	13. Hands-on: Real-time translation (Amazon Translate)	5:31
	14. Hands-on: Batch job translation (Amazon Translate)	9:12

Practice Exam, Exam Tips & Scheduling
	1. Exam Signup & Get 30min more time!	8:10
	2. Final Exam Tips	7:16

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AWS Certified Machine Learning Engineer - Associate MLA-C01

Curriculum For This Course

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