02 · Curriculum
What's in the course.
- From Monolithic Legacies to AI-Native Microservices40m
- From Monolithic Legacies to AI-Native Microservices - Slide Deck (PDF)Deck
Intermediate
Building AI Systems with Microservices on AWS
This course explores the convergence of AI and microservices, teaching you to design scalable, cloud-native AI systems using AWS. Learn RAG, agentic workflows, latency optimization, state management, and production-ready deployment pattern…
- 5+
- enrolled
- 3 hrs
- of instruction
- 8
- lectures
- 5
- modules
Taught by Abhishek Kumar01 · What you'll be able to do
Four things you can ship afterwards.
This course explores the convergence of AI and microservices, teaching you to design scalable, cloud-native AI systems using AWS. Learn RAG, agentic workflows, latency optimization, state management, and production-ready deployment patterns for enterprise-grade intelligent applications.
Architect AI-native microservices
Architect AI-native microservices that integrate LLMs, RAG, and agentic workflows into enterprise systems.
Design for latency state
Design for latency, state management, and probabilistic-deterministic integration challenges.
Implement event-driven serverless AI
Implement event-driven, serverless AI architectures using AWS (Bedrock, SageMaker, Lambda, EKS/ECS).
Build intelligent customer support
Build intelligent customer support systems with feedback loops, observability, and production-grade governance.
03 · Instructors
Taught by the people who built it.
Abhishek Kumar
All courses by Abhishek04 · Is it for you?
Who it's for, and what to bring.
Built for
- Cloud Architects designing AI-enabled enterprise systems.
- Backend / Microservices Developers integrating LLM APIs.
- AI/ML Engineers deploying models in production.
- DevOps / Platform Engineers managing distributed AI workloads.
- Technical Product Managers leading AI transformation initiatives.
- Engineering Leaders modernizing legacy systems into AI-native architectures.
Bring with you
- Basic understanding of cloud computing (preferably AWS fundamentals).
- Familiarity with microservices concepts (REST APIs, containers, distributed systems).
- Introductory knowledge of AI/ML or LLM concepts (helpful but not deeply mathematical).
- Comfort with system architecture diagrams and high-level technical discussions.
05 · FAQ
Before you enrol.
Each of the 5 modules is a recorded live session, with slide deck and handouts, readings from that session. Watch at your own pace.
$49.00
Related credentials
The Chartered Data Scientist (CDS™) Designation
Achieve the highest distinction in the data science profession.
ADaSci Certified Data Engineer (ACDE)
The ADaSci Certified Data Engineer program is a 30-hour self-paced online certification designed to build practical expertise in modern data engineering. It offers end-to-end training in designing scalable data pipelines, managing cloud infrastructure, and ensuring data quality and governance.
Ready to start?
$49, or free with Premium membership.