Understand cloud data architectures across AWS, Azure and GCP, and deploy one guided reference pipeline using AWS. 1. Who can join Suitable for: Data engineers, cloud practitioners and solution architects Mandatory prerequisites: Python/SQL basics, networking and introductory cloud concepts 2. Duration 52 live hours • Approximately 9 weeks at 6 hours per week; actual timetable to be confirmed. 3. Mode Classroom - Thaiyur / Kelambakkam, OMR Chennai (subject to schedule) Live Online (subject to schedule)
4. Syllabus — five modules
Module 1: Cloud Storage & Data Lake Foundations (S3 / Blob Storage / GCS) Learning outcome: Map cloud storage and lake components across major providers. Module 2: Serverless Data Ingestion (AWS Glue, Lambda, Azure Data Factory) Learning outcome: Design and run an introductory serverless ingestion flow. Module 3: Cloud Data Warehousing (Redshift, Synapse, BigQuery) & Performance Tuning Learning outcome: Compare warehouse designs and implement a chosen lab example. Module 4: Identity & Access Management (IAM), Encryption & Cloud Security Learning outcome: Apply least-privilege IAM, encryption and secret-handling basics. Module 5: FinOps: Cost Management, Monitoring & Cloud Architecture Optimization Learning outcome: Estimate cloud costs and configure budget guardrails. 5. Practical project Source capstone title: Design & Deploy an Enterprise Serverless Cloud Data Pipeline on AWS Student deliverable: A sample AWS serverless data pipeline taking input files to cloud storage, transforming them and exposing query-ready output with cost controls.
6. What is included Live trainer-led sessions Practical assignments Sample code or templates, as applicable Project feedback Learning assessment Perizona course-completion certificate subject to assessment 7. Upcoming batch Start date: To be announced. Students can register interest; dates are shared only after confirmation.
