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1.
Worklog - AWS Learning Journey
1.1.
Week 1 - Cloud Computing Fundamentals
1.1.1.
Day 01 - Introduction to Cloud Computing
1.1.2.
Day 02 - AWS Global Infrastructure
1.1.3.
Day 03 - AWS Management Tools
1.1.4.
Day 04 - Cost Optimization on AWS
1.1.5.
Day 05 - AWS Well-Architected Framework
1.2.
Week 2 - AWS Networking Services
1.2.1.
Day 06 - Amazon VPC Fundamentals
1.2.2.
Day 07 - VPC Routing & Network Interfaces
1.2.3.
Day 08 - VPC Security & Flow Logs
1.2.4.
Day 09 - VPC Connectivity & Load Balancing
1.2.5.
Day 10 - Elastic Load Balancing
1.3.
Week 3 - AWS Compute Services
1.3.1.
Day 11 - Amazon EC2 Fundamentals
1.3.2.
Day 12 - EC2 Storage & Backup
1.3.3.
Day 13 - Instance Store & User Data
1.3.4.
Day 14 - EC2 Auto Scaling
1.3.5.
Day 15 - Lightsail, EFS & FSx
1.4.
Week 4 - AWS Storage Services
1.4.1.
Day 16 - Amazon S3 Fundamentals
1.4.2.
Day 17 - S3 Advanced Features
1.4.3.
Day 18 - AWS Snow Family & Hybrid Storage
1.4.4.
Day 19 - Disaster Recovery on AWS
1.4.5.
Day 20 - AWS Backup & FSx
1.5.
Week 5 - AWS Security & Identity
1.5.1.
Day 21 - Shared Responsibility & IAM Basics
1.5.2.
Day 22 - IAM Policies & Roles
1.5.3.
Day 23 - Amazon Cognito & Organizations
1.5.4.
Day 24 - SCPs, Identity Center & KMS
1.5.5.
Day 25 - AWS Security Hub & Automation
1.6.
Week 6 - AWS Database Services
1.6.1.
Day 26 - Database Fundamentals
1.6.2.
Day 27 - Amazon RDS & Aurora
1.6.3.
Day 28 - Amazon Redshift
1.6.4.
Day 29 - Amazon ElastiCache
1.6.5.
Day 30 - Database Migration & Best Practices
1.7.
Week 7 - Vertical Slice Delivery
1.7.1.
Day 31 - Vertical Slice Kickoff
1.7.2.
Day 32 - Contract-First & Mocking
1.7.3.
Day 33 - Next.js App Router
1.7.4.
Day 34 - FastAPI Clean Architecture
1.7.5.
Day 35 - Contract Testing & Retrospective
1.8.
Week 8 - Natural Language Processing & Deep Learning
1.8.1.
Day 36 - NLP Foundations & Applications
1.8.2.
Day 37 - Voice Search & Chatbot Architecture
1.8.3.
Day 38 - Seq2seq Models & LSTM Deep Dive
1.8.4.
Day 39 - NMT & Text Summarization
1.8.5.
Day 40 - MT Evaluation & Decoding Strategies
1.9.
Week 9 - Transformer Architecture & Implementation
1.9.1.
Day 41 - RNN Problems & Why Transformers Are Needed
1.9.2.
Day 42 - Transformer Architecture Overview
1.9.3.
Day 43 - Scaled Dot-Product Attention Deep Dive
1.9.4.
Day 44 - Attention Types: Self, Masked, and Encoder-Decoder
1.9.5.
Day 45 - Transformer Decoder & GPT2 Implementation
1.10.
Week 10 - Transfer Learning, BERT & T5
1.10.1.
Day 46 - Transfer Learning Fundamentals
1.10.2.
Day 47 - Question Answering Modes
1.10.3.
Day 48 - BERT Bidirectional Context
1.10.4.
Day 49 - T5 Text-to-Text Multitask
1.10.5.
Day 50 - Fine-Tuning Practice
1.11.
Week 11 - Lambda Managed Instances & AWS re:Invent Learnings
1.11.1.
Day 51 - Lambda Managed Instances Overview
1.11.2.
Day 52 - Capacity Provider Setup
1.11.3.
Day 53 - Functions on LMI
1.11.4.
Day 54 - Networking & Observability
1.11.5.
Day 55 - Scaling & Ops Playbook
1.12.
Week 12 - AWS re:Invent 2025 Announcements
1.12.1.
Day 56 - Nova Models & Agent Launches
1.12.2.
Day 57 - Bedrock Models & AgentCore
1.12.3.
Day 58 - Vectors & Privacy Data
1.12.4.
Day 59 - SageMaker AI Platform
1.12.5.
Day 60 - Compute Launches
2.
Proposal
3.
Translated Blogs
3.1.
Accelerate Your Data and AI Flow by Connecting Amazon SageMaker Unified Studio to Visual Studio Code
3.2.
Announcing Amazon EC2 M4 and M4 Pro Mac Instances
3.3.
Tuning Guide for AMD-based Amazon EC2 Instances
4.
Events Participated
Event 1 - Vietnam Cloud Day 2025
Event 2 - AWS GenAI Builder Club: AI-Driven Development Life Cycle
5.
Workshop
5.1.
Introduction
5.2.
Prerequisite
5.3.
Lambda Basics
5.3.1
Lambda Hello World (Node.js)
5.3.2
Lambda Hello World (Python)
5.4.
API Gateway Integration
5.4.1
Create REST API
5.4.2
Add POST Method
5.4.3
Test API Gateway
5.4.4
Optional: CORS & Custom Domain
5.5.
Sample App Logic
5.6.
Clean up
6.
Self-Assessment
7.
Sharing and Feedback
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> Clean up
Cleanup Steps
Cost Notes
Clean up
Cleanup Steps
Delete the API Gateway stage/API created for the workshop.
Delete the Lambda functions (Node.js, Python, suggest).
Remove IAM roles/policies created specifically for Lambda (if no longer needed).
Check CloudWatch Log Groups, set short retention or delete.
Ensure no remaining resources that incur costs (temporary S3 buckets, temporary Secrets if any).
Cost Notes
Lambda/Logs/API Gateway have low costs but should still be deleted after the lab.
If you created additional resources (S3, KMS), confirm they have been deleted/retention set.