AI Architecture Masterclass

Stop Building Demos.
Ship Production AI.

Most courses teach you to call an API. Real companies build systems. Learn how to architect, deploy, and scale AI Softwares using production-grade patterns.

Start Learning for $10 $50
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AI Software Architecture

CURRENT STATUS

Production Ready

DISCOUNT

80% OFF

Learn the Production Stack

Docker Kubernetes FastAPI LangChain VectorDB CI/CD Docker Kubernetes FastAPI LangChain VectorDB CI/CD

The "Demo Trap" is Real

The Hobbyist Way

  • Hardcoded prompts in scripts
  • Running local .py files
  • No error handling or retries
  • Breaks with >1 concurrent user

The Engineering Way

  • Event-driven Architecture
  • Containerized (Docker/K8s)
  • Observability & Eval built-in
  • Auto-scaling & Self-healing

Architectural Blueprint

Not just "how to code", but "how to design systems".

ver: production_v1.0

End-to-End System Design

Move beyond simple RAG tutorials. Learn how the pieces fit together: Ingestion, Vector Stores, Retrieval, Generation, and the API layer that exposes it all to the world.

  • > Microservices vs Monoliths
  • > Async Pipeline Design

Agents vs. Workflows

Understand when to let the LLM decide (Agents) and when to constrain it (Workflows).

Tool Calling Runtime

Deep dive into how models actually execute code and interact with external APIs safely.

Production Infrastructure

The boring stuff that makes money. CI/CD pipelines, Docker containers, Kubernetes orchestration, and load balancing.

Reliability

Self-healing systems, fallbacks, and managing hallucinations in prod.

API Layer

Building robust interfaces using FastAPI architecture.

DataSense
4.8 Rating

DataSense LMS

A community-driven platform dedicated to helping individuals grow in Data Analytics, Machine Learning, and AI. We don't just teach theory; we focus on engaging events, challenges, and real-world case studies to bridge the gap between learning and doing.

Followers: 24,000+
Bookings: 1,622+
Avg. Response: 48h

Common Questions

This is an intermediate-to-advanced overview. You should have some familiarity with Python and basic LLM concepts (prompts, models). The focus is on architecture and production engineering, not "Hello World" in Python.
We skip the toy examples. We discuss CI/CD pipelines, Dockerization, Kubernetes scaling, observability, and cost management—the things that actually matter when you deploy AI in a company.
We strive for 100% satisfaction. Given the digital nature and low price point ($10), please check the curriculum carefully. If you have valid concerns post-purchase, reach out to us directly.

Ready to Architect the Future?

Join the masterclass today and stop building toys. Your engineering career awaits.

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