English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 281 lectures (22h 40m) | 10.04 GB
Hands-on GenAI development on AWS with Bedrock, SageMaker, and Flows – includes a complete 75-question practice exam.
This course contains the use of artificial intelligence for authoring assistance, but all content is human-reviewed. No AI avatars or synthetic voices are used.
Become an AWS-certified generative AI professional with the most comprehensive preparation available for the AWS Certified Generative AI Developer – Professional (AIP-C01 / AP1-C01) exam. This course gives you everything you need—hands-on practice, deep technical coverage, and complete alignment with the official exam guide.
What You’ll Learn
Generative AI on AWS blends the world’s most popular cloud platform with cutting-edge AI techniques. This course helps you master both—through real scenarios, guided examples, and practical architecture patterns. You’ll learn how to:
- Build GenAI applications using Amazon Bedrock, SageMaker, and Knowledge Bases
- Design agentic AI systems using Bedrock Agents, Flows, OpenSearch, Strands, Agent Squad, and AgentCore
- Apply optimization techniques for RAG pipelines, embedding strategies, and foundation model performance
- Manage prompts and structured workflows using Prompt Management and Bedrock Flows
- Evaluate model quality and safety using Bedrock Evaluations
- Prepare and process data with Bedrock Data Automation, SageMaker, Glue, Comprehend, Textract, and more
- Orchestrate production-grade AI systems using Step Functions, Lambda, Pipelines, and CI/CD tools
Every module is grounded in the AWS exam domains and the skills described in AWS’s official documentation. We’ve mapped the entire exam blueprint to ensure you don’t miss a thing.
If you’re ready to master generative AI on AWS and earn one of the most forward-looking certifications available, we’re excited to guide you every step of the way. Let’s get started!
Who this course is for:
- AWS developers, cloud engineers, and architects preparing for the Generative AI Developer Professional exam.
- AI and ML practitioners who want to build real GenAI applications using Bedrock, SageMaker, and RAG patterns.
- Technical professionals adopting generative AI and seeking hands-on experience with AWS tools and best practices.
- Learners familiar with AWS fundamentals who want to advance into production-grade GenAI development.
Table of Contents
Introduction
1 Course Overview
2 Get the Course Materials
3 Setting Up an AWS Billing Alarm
Generative AI Fundamentals and Bedrock
4 Section Intro
5 Amazon Bedrock Overview
6 Hands-On with the Bedrock Playground
7 Fine-Tuning Foundation Models in Bedrock
8 Low-Rank Adaptation (LoRA) – How Fine-Tuning Works
9 Retrieval-Augmented Generation (RAG)
10 Vector Stores and Semantic Search
11 Bedrock Knowledge Bases
12 Hands-On with Knowledge Bases
13 Pre-Retrieval and Chunking Strategies
14 Managing Chunking with Bedrock
15 Optimizing your Vector Store and Embeddings
16 Evaluating RAG Performance
17 Mulitmodal Models and Pipelines with Bedrock
18 Bedrock Guardrails
19 Hands-On with Bedrock Guardrails
20 Token-Level Redaction
21 Amazon Bedrock Prompt Management
22 Bedrock Prompt Flows
23 Enforcing Use of Structured Data
24 Intro to Prompt Engineering
25 Anatomy of a Prompt
26 Prompt Best Practices
27 Types of Prompts
28 Prompt Misuse and Mitigating Bias
29 Enterprise Integration
30 AWS Well-Architected Tool Generative AI Lens
Managing Data for Generative AI
31 Section Intro
32 Dealing with Structured Data
33 Amazon Bedrock Data Automation
34 SageMaker Data Wrangler
35 Hands On SageMaker Data Wrangler
36 AWS Glue
37 AWS Glue Studio
38 Glue Data Quality
39 CloudWatch Metrics
40 AWS Transcribe
41 AWS Transcribe – Hands On
42 Amazon Comprehend
43 Amazon Comprehend – Hands On
44 Using Comprehend, Lambda, and Bedrock together
45 Intro to vector DB’s
46 Introducing Amazon OpenSearch Service (part 1)
47 Introducing Amazon OpenSearch Service (part 2)
48 OpenSearch Index Management and Designing for Stability
49 Amazon OpenSearch Service Performance
50 Amazon OpenSearch Serverless
51 Using and Tuning OpenSearch as a Vector Store
52 Amazon RDS
53 Amazon RDS – Hands On
54 Amazon RDS with S3 Document Repositories
55 Amazon Aurora
56 Amazon Aurora – Hands On
57 Amazon Aurora and the pgvector Extension
58 Amazon DynamoDB
59 Amazon DynamoDB – Hands On
60 Amazon DynamoDB – WCU & RCU
61 Amazon DynamoDB – WCU & RCU – Hands On
62 Amazon DynamoDB – Basic APIs
63 Amazon DynamoDB – Basic APIs – Hands On
64 Amazon DynamoDB DAX
65 Amazon DynamoDB DAX – Hands On
66 Amazon DynamoDB – TTL
67 DynamoDB and Generative AI
68 Keeping your Vector Store Up to Date
69 Re-Ranker Modules in Bedrock
70 Amazon S3 – Storage Classes
71 Amazon S3 – Storage Classes – Hands On
72 Amazon S3 – Lifecycle Rules
73 Amazon S3 – Lifecycle Rules – Hands On
74 Amazon S3 – Replication
75 Amazon S3 – Replication – Notes
76 Amazon S3 – Replication – Hands On
Agentic AI
77 Section Intro
78 LLM Agents in Bedrock
79 Hands On Amazon Bedrock Agents
80 Multi-Agent Workflows
81 Short and Long-Term Agent Memory
82 Strands Agents
83 Agent Squad
84 Amazon AgentCore Introduction
85 AgentCore Memory and Tools
86 AgentCore Bedrock Import, Gateway, and Identity
87 Lab Strands Agents, Amazon Bedrock AgentCore, Agent Squad
88 Model Context Protocol (MCP)
89 OpenAPI and Tool Usage
90 Humans in the Loop
91 Amazon Q Business
92 Amazon Q Business – Hands On
93 Amazon Q Apps
94 Amazon Q Apps – Hands On
95 Amazon Q Business – Cleanup
96 Amazon Q Developer
97 Amazon Q Developer – Hands On
Operational Efficiency and Optimization
98 Section Intro
99 Token Efficiency
100 Cost-Effective Model Selection
101 Maximizing Resource Utilization and Throughput
102 Intelligent Caching Systems for GenAI
103 Building Responsive AI Systems
104 Optimizing Retrieval Performance
105 Optimizing for Specific Use Cases
106 Optimizing Foundation Model System Performance
107 Exponential Backoff and Connection Pooling
108 Amazon Bedrock Cross-Region Inference
Managing Models with SageMaker AI
109 Section Intro
110 Data Processing, Training, and Deployment with SageMaker
111 SageMaker Deployment Safeguards
112 Optimizing Foundation Model Deployments
113 SageMaker Ground Truth
114 SageMaker Model Monitor and Clarify
115 SageMaker Model Registry
116 SageMaker Lineage Tracking
117 Cross-Account Lineage Tracking
118 SageMaker on the Edge (Neo)
119 SageMaker Unified Studio
120 SageMaker Pipelines
121 Hands On SageMaker JumpStart
More Tools for Building AI Applications
122 Section Intro
123 AWS Lambda
124 Lambda Integration Patterns, Part 1
125 Lambda Integration Patterns, Part 2
126 Lambda with Bedrock
127 Amazon API Gateway
128 Amazon API Gateway – Hands On
129 Amazon API Gateway and Generative AI Applications
130 AWS AppConfig
131 Dynamic FM Selection with AppConfig
132 AWS Step Functions
133 Step Function States
134 Step Functions Circuit Breaker Pattern
135 Lab Prompt Chaining with Step Functions and Bedrock
136 AWS CodePipeline
137 AWS CodePipeline – Hands On – Prerequisites
138 AWS CodePipeline – Hands On
139 AWS CodeBuild
140 AWS CodeBuild – Hands On – Part 1
141 AWS CodeBuild – Hands On – Part 2
142 AWS CodeDeploy
143 AWS CodeDeploy – Hands On
144 MLFlow for LLM Experimentation
145 AWS AppSync and GenAI
146 AWS Outposts
147 AWS Outposts and GenAI
148 AWS Wavelength
149 AWS Wavelength and GenAI
150 Amazon SQS
151 Amazon SQS – Hands On
152 AWS Amplify
153 Amazon EventBridge
154 Amazon EventBridge – Hands On
155 Amazon SNS
156 Amazon SNS – Hands On
157 Amazon AppFlow
Governance and QA
158 Section Intro
159 Bedrock Agent Tracing
160 Evaluation Techniques for Foundation Models
161 Evaluating LLM’s with ROUGE, BLUE, and BERT scores
162 Amazon Bedrock Model Evaluations
163 Deployment Validation Systems
164 Principles of Responsible AI
165 CloudWatch Logs
166 CloudWatch Logs – Hands On
167 CloudWatch Alarms
168 CloudWatch Alarms – Hands On
169 CloudWatch RUM
170 CloudWatch and GenAI Monitoring
171 AWS CloudTrail
172 AWS CloudTrail – Hands On
173 CloudTrail and GenAI
174 AWS X-Ray
175 AWS X-Ray – Hands On
176 AWS Lake Formation
Security, Identity, and Compliance
177 Section Intro
178 Principle of Least Privilege
179 Data Masking and Key Salting
180 IAM Introduction Users, Groups, Policies
181 IAM Users & Groups – Hands On
182 AWS Console Simultaneous Sign-in
183 IAM Policies
184 IAM Policies – Hands On
185 IAM MFA
186 IAM MFA – Hands On
187 IAM Roles
188 IAM Roles – Hands On
189 Encryption 101
190 AWS KMS
191 AWS KMS – Hands On
192 Amazon Macie
193 AWS Secrets Manager
194 AWS Secrets Manager – Hands On
195 Amazon Cognito
196 AWS WAF
197 VPC, Subnets, Internet Gateway, NAT Gateway
198 NACL, Security Groups, VPC Flow Logs
199 VPC Peering, Endpoints, VPN, Direct Connect
200 VPC Cheat Sheet & Closing Comments
201 AWS PrivateLink
Analytics Services You Should Know
202 Intro Other Services You Should Know
203 Amazon Athena
204 Amazon EMR
205 Amazon Quicksight
206 Amazon Kinesis Data Streams
207 Amazon Kinesis Data Streams – Hands On
208 Amazon MSK
Compute, Container, and Customer Engagement Services You Should Know
209 AWS App Runner
210 AWS App Runner – Hands On
211 Amazon EC2
212 Amazon EC2 – Hands On
213 Amazon ECS
214 Creating ECS Cluster – Hands On
215 Creating ECS Service – Hands On
216 Amazon EKS
217 Amazon EKS – Hands On
218 Amazon Lex + Connect
Database Services You Should Know
219 Amazon DocumentDB
220 Amazon ElastiCache
221 Amazon ElastiCache – Hands On
222 Amazon Neptune
223 Amazon Neptune Analytics and Vector Search
Developer Tools Services You Should Know
224 AWS CDK
225 AWS CDK – Hands On
226 AWS Access Keys, CLI and SDK
227 AWS CLI Setup on Windows
228 AWS CLI Setup on Mac
229 AWS CLI Setup on Linux
230 AWS CLI – Hands On
231 AWS CloudFormation
232 AWS CloudFormation – Hands On
233 AWS CodeArtifact
234 AWS CodeArtifact – Hands On
Machine Learning Services You Should Know
235 Amazon Augmented AI
236 Amazon Augmented AI – Hands On
237 Amazon Kendra
238 Amazon Lex
239 Amazon Lex – Hands On
240 Amazon Rekognition
241 Amazon Rekognition – Hands On
242 Amazon Textract
243 Amazon Textract – Hands On
244 Amazon Transcribe
245 Amazon Transcribe – Hands On
Management and Governance Services You Should Know
246 AWS Auto Scaling
247 AWS Auto Scaling – Hands On
248 AWS Cost Anomaly Detection
249 AWS Cost Explorer
250 Amazon Managed Grafana
251 AWS Systems Manager
252 AWS Systems Manager – Session Manager
253 AWS Systems Manager – Parameter Store
Migration and Transfer Services You Should Know
254 AWS DataSync
255 AWS Transfer Family
Networking and Content Delivery Services You Should Know
256 Amazon CloudFront
257 Amazon CloudFront – Hands On
258 Amazon Elastic Load Balancing
259 Amazon Elastic Load Balancing – Hands On
260 AWS Global Accelerator
261 AWS Global Accelerator – Hands On
262 Amazon Route 53
263 Amazon Route 53 – Registering a Domain
264 Amazon Route 53 – Creating our First Records
265 Amazon Route 53 – EC2 Setup
Storage Services You Should Know
266 Amazon EBS
267 Amazon EBS – Hands On
268 Amazon EFS
269 Amazon EFS – Hands On
270 Amazon EFS vs. Amazon EBS
Practice Exam
Wrapping Up
271 Intro Getting Ready for the Exam
272 More Preparation Resources and the Exam Guide
273 New Question Types
274 Test-Taking Tips
275 Exam Walkthrough and Signup
276 Save 50% on your AWS Exam Cost!
277 Get an Extra 30 Minutes on your AWS Exam – Non Native English Speakers Only
278 AWS Certification Paths
279 Congratulations!
280 Bonus Lecture
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