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Module 8 — AI, ML and Data Analytics

Status: ⬜ upcoming · Domain 3 · We'll deepen this and build a visual page when we study it.

AI / ML services (mostly "know what each does")

• Amazon SageMaker — build, train, and deploy your own ML models end to end.
• Amazon Lex — conversational AI / chatbots (the tech behind Alexa).
• Amazon Kendra — ML-powered intelligent search over your documents.
• Amazon Comprehend — NLP: extract sentiment, entities, key phrases from text.
• Amazon Rekognition — analyze images/video (objects, faces, moderation).
• Amazon Polly — text → speech. Amazon Transcribe — speech → text. Amazon Translate — language translation.
• Amazon Textract — extract text/data from scanned documents.

Analytics services

• Amazon Athena — run SQL queries directly on S3 data (serverless).
• AWS Glue — ETL (extract, transform, load) — prepare/integrate data.
• Amazon Kinesis — collect/process real-time streaming data (logs, video, telemetry).
• Amazon QuickSight — BI dashboards and visualizations.
• Amazon EMR — big-data processing (Hadoop/Spark).
• (Redshift = the data warehouse, see Module 7.)

Likely exam framing

• Build/train your own model → SageMaker. Chatbot → Lex. Search → Kendra.
• Image recognition → Rekognition. Text↔speech → Polly / Transcribe.
• SQL on S3 → Athena. ETL → Glue. Real-time streams → Kinesis. Dashboards → QuickSight.