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Notes will be added here as AWS topics are studied (MLA-C01 exam track, 12-week plan)

Resources

ResourceTypeCostUse
Stephane Maarek — AWS MLA-C01Udemy course~₹499 on salePrimary course (buy W02+)
FreeCodeCamp AWS on YouTubeVideoFreeW01 IAM + S3 supplement
AWS Skill BuilderOfficial practiceFree tierPractice questions
Exam Topics (examtopics.com)Practice Q&AFreeExam prep (W10+)
Service / AreaNotes
IAM[[IAM]] ✅
S3[[S3]]
EC2[[EC2]] ✅
VPC—
Lambda—
API Gateway—
SageMaker[[ML Associate Exam/02 - Model Development]] ✅
Bedrock[[ML Associate Exam/06 - AWS AI Services]] ✅

ML Associate Exam Notes

FileCoverage
[[ML Associate Exam/00 - Index & Exam Guide]]Exam overview, service map, key numbers
[[ML Associate Exam/01 - Data Preparation]]Glue, S3, Kinesis, Ground Truth, Feature Store (Domain 1 — 28%)
[[ML Associate Exam/02 - Model Development]]SageMaker training, algorithms, HPO, JumpStart (Domain 2 — 26%)
[[ML Associate Exam/03 - Deployment & MLOps]]Endpoints, Pipelines, CI/CD, inference types (Domain 3 — 22%)
[[ML Associate Exam/04 - Monitoring & Security]]Model Monitor, Clarify, drift, security (Domain 4 — 24%)
[[ML Associate Exam/05 - ML Fundamentals]]Core ML concepts, algorithms, metrics, feature engineering
[[ML Associate Exam/06 - AWS AI Services]]Rekognition, Comprehend, Bedrock, Forecast, Personalize

Study Plan

WeekAWS Topic
W1 (Mar 18–22)IAM + S3
W2 (Mar 23–29)EC2
W3 (Mar 30–Apr 5)VPC + RDS
W4 (Apr 6–12)Lambda + API Gateway
W5 (Apr 13–19)CloudWatch + SQS/SNS
W6 (Apr 20–26)SageMaker basics
W7 (Apr 27–May 3)Bedrock
W8–W11MLOps, Feature Store, Exam Cram
W12 (Jun 2–8)MLA-C01 Exam

MLA-C01 Exam Domains

DomainWeight
Data Engineering28%
Exploratory Data Analysis24%
Modeling28%
ML Implementation & Operations20%

Key services: SageMaker, Bedrock, Rekognition, Comprehend, Forecast, S3, Glue, Athena, Step Functions

Core Concepts Checklist

IAM ✅ 2026-03-22

  • Users, Groups, Roles, Policies
  • Least privilege principle
  • IAM roles for EC2 / Lambda (no hardcoded credentials)
  • STS assume-role
  • Service Control Policies (SCP) — cover when doing advanced IAM

S3

  • Buckets, objects, keys, regions
  • Storage classes — Standard, Standard-IA, Glacier Instant, Glacier Flexible, Deep Archive
  • Lifecycle policies — auto-transition between storage classes
  • Versioning + MFA delete
  • Replication — CRR (cross-region) vs SRR (same-region)
  • Encryption — SSE-S3, SSE-KMS, SSE-C, client-side
  • Presigned URLs
  • S3 Select / Athena queries

EC2

  • Instance types (C = compute, M = general, R = memory, G = GPU)
  • On-demand vs Reserved vs Spot
  • AMI, EBS volumes, security groups
  • Auto Scaling Groups + Load Balancer

VPC

  • Subnets (public/private), route tables, internet gateway
  • NAT gateway
  • Security groups vs NACLs
  • VPC peering, PrivateLink

Lambda

  • Trigger types (API GW, S3 event, SQS, EventBridge)
  • Cold starts, concurrency limits
  • Layers, environment variables

SageMaker

  • Training jobs, model artifacts, endpoints
  • Built-in algorithms (XGBoost, Linear Learner, etc.)
  • SageMaker Pipelines
  • Feature Store, Model Registry, Model Monitor

Bedrock

  • Foundation models (Claude, Titan, Llama, etc.)
  • Inference API vs Provisioned Throughput
  • Knowledge Bases (RAG)
  • Agents