03 — Curriculum
Course content
5 sections · 12 lectures
ADaSci Academy
Architectural Patterns in CrewAI and Autogen
This course explores the architectural foundations of agentic AI systems by contrasting CrewAI’s role-based orchestration with AutoGen’s conversation-driven reasoning. You will move from theoretical concepts to hands-on…
2,543+ enrolled
3 hours
Intermediate
01 — Overview
About this course
This course explores the architectural foundations of agentic AI systems by contrasting CrewAI’s role-based orchestration with AutoGen’s conversation-driven reasoning. You will move from theoretical concepts to hands-on implementation, building structured workflows and dynamic multi-agent loops while understanding production tradeoffs, determinism, debugging, and scalability.
02 — Outcomes
What you'll learn
✓
When to choose structured orchestration, dynamic collaboration, or hybrid architectures✓
How AutoGen enables emergent reasoning through agent interaction✓
How CrewAI enforces structured task execution and deterministic workflows✓
Architectural differences between pipeline orchestration and conversational loops✓
The paradigm shift from passive LLM prompts to autonomous multi-step agent systems04 — Prerequisites
Requirements
- Working knowledge of APIs and environment setup
- Basic Python programming knowledge
- Familiarity with LLM concepts such as prompts and API usage
- Understanding of software architecture fundamentals
05 — Audience
Who should take this course
- AI engineers building multi-agent applications
- Software architects designing AI-native systems
- Developers transitioning from prompt engineering to agent orchestration
- Technical leaders evaluating CrewAI versus AutoGen for production use
$49.00
Member Pricing
FREE with Premium
50% off with General
Duration3h
LevelIntermediate
$49.00