Master advanced multi-agent AI systems using CrewAI and AutoGen to design, orchestrate, and deploy autonomous agent workflows for real-world enterprise use cases.
Master advanced multi-agent AI systems using CrewAI and AutoGen to design, orchestrate, and deploy autonomous agent workflows for real-world enterprise use cases.
Level
Advanced
Duration
8 weeks
















Advanced Multi-Agent Orchestration (The “CrewAI & AutoGen” Expert) is a specialized, industry-aligned program designed for professionals who want to build, manage, and scale autonomous AI agent systems. This course goes far beyond single-agent LLM usage and focuses on collaborative intelligence, where multiple agents communicate, reason, delegate tasks, and self-correct within complex workflows. Learners will gain deep expertise in CrewAI and Microsoft AutoGen, understanding agent roles, memory, planning strategies, tool execution, and feedback loops. The curriculum emphasizes real-world orchestration patterns such as hierarchical agents, swarm intelligence, role-based delegation, and event-driven coordination. You will also explore evaluation, debugging, security, and cost optimization strategies critical for production deployments. By the end of the course, you will be capable of architecting robust multi-agent systems for research automation, data analysis, software development, customer operations, and decision intelligence. Delivered through hands-on labs and enterprise-grade projects on Jast Tech, this course prepares you for cutting-edge AI engineering and applied agentic system roles.
Advanced Multi-Agent Orchestration (The “CrewAI & AutoGen” Expert) is a specialized, industry-aligned program designed for professionals who want to build, manage, and scale autonomous AI agent systems. This course goes far beyond single-agent LLM usage and focuses on collaborative intelligence, where multiple agents communicate, reason, delegate tasks, and self-correct within complex workflows. Learners will gain deep expertise in CrewAI and Microsoft AutoGen, understanding agent roles, memory, planning strategies, tool execution, and feedback loops. The curriculum emphasizes real-world orchestration patterns such as hierarchical agents, swarm intelligence, role-based delegation, and event-driven coordination. You will also explore evaluation, debugging, security, and cost optimization strategies critical for production deployments. By the end of the course, you will be capable of architecting robust multi-agent systems for research automation, data analysis, software development, customer operations, and decision intelligence. Delivered through hands-on labs and enterprise-grade projects on Jast Tech, this course prepares you for cutting-edge AI engineering and applied agentic system roles.
Job Roles You Can Achieve
After completing this course
Foundations of Multi-Agent Systems
Introduces theoretical and practical foundations of multi-agent AI systems and why orchestration is critical for complex problem-solving.
LLMs as Agents
Focuses on converting LLMs into reliable agents with defined roles, tools, and decision boundaries.
CrewAI Architecture Deep Dive
Provides hands-on mastery of CrewAI’s orchestration primitives and workflow design patterns.
AutoGen Framework Internals
Explores AutoGen’s agent-to-agent communication model and advanced coordination techniques.
Advanced Orchestration Patterns
Teaches proven orchestration strategies used in research, coding, and enterprise automation.
Seven intentional milestones — from first session to dream job.
Hands-on experience with real-world scenarios designed for mastery.
Autonomous Research & Report Generation Crew
AI Software Development Agent Team
Enterprise Decision-Support Agent System

Antigravity

Machine Learning

Agentic AI

Python
Select a schedule that works best for you
Starts
23 May 2026
Time
09:30 AM – 12:30 PM
Duration
8 weeks
Starts
25 May 2026
Time
07:00 AM – 09:00 AM
Duration
8 weeks
Starts
30 May 2026
Time
02:00 PM – 05:00 PM
Duration
8 weeks
Starts
01 Jun 2026
Time
08:00 PM – 10:00 PM
Duration
8 weeks
Our team will craft the perfect batch for you.
Real Feedback from our clients
Round-the-clock assistance
Professional profile building
Expert resume crafting
Mentorship from graduates
Mock interviews & tips
Real-world experience



Advanced Multi-Agent Orchestration (The "CrewAI & AutoGen" Expert) – Associate
SAA-C03
130 minutes
Multiple Choice & Multi-Response
720 (Scale: 100–1000)
Associate

Prepare
Curated questions with expert answers to help you ace your next interview.
Q1. What problem do multi-agent systems solve compared to single-agent LLMs?
They enable task decomposition, parallel reasoning, role specialization, and improved reliability for complex workflows.
Q2. How does CrewAI differ from AutoGen?
CrewAI emphasizes structured task orchestration with defined roles, while AutoGen focuses on conversational agent interactions and dynamic workflows.
Q3. What is a planner-executor pattern?
A design where one agent plans tasks and delegates execution to specialized agents, improving accuracy and efficiency.
Q4. How do you manage memory in multi-agent systems?
By combining short-term context, long-term vector memory, and shared knowledge stores across agents.
Q5. What are common failure modes in agent orchestration?
Hallucinations, infinite loops, tool misuse, context loss, and cost overruns, mitigated through evaluation and guardrails.
Support
Can't find what you're looking for? Reach out to our support team anytime.
Q1. Is prior AI or LLM experience required?
Yes, familiarity with Python and basic LLM concepts is recommended to fully benefit from advanced orchestration topics.
Q2. Does this course focus more on theory or practice?
It is highly practical, with real-world orchestration patterns, labs, and production-style projects.
Q3. Are CrewAI and AutoGen both covered in depth?
Yes, the course provides deep, hands-on coverage of both frameworks and compares their strengths.
Q4. Can these skills be applied in enterprise environments?
Absolutely, the course emphasizes scalability, security, evaluation, and real deployment scenarios.
Q5. What roles does this course prepare me for?
AI Engineer, Agentic Systems Architect, Applied GenAI Engineer, and Automation Architect.
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JastTech
Training & Development Center
Plot no 9, IT Park, Madhapur, Hyderabad, Telangana 500081
JastTech
Training & Development Center
Office 402, Tech Park Road, Hinjewadi, Pune, Maharashtra 411057
JastTech
Training & Development Center
Millenium City - Tower I, Salt Lake, Kolkata, West Bengal 700091
JastTech
Training & Development Center
Plot no 9, IT Park, Madhapur, Hyderabad, Telangana 500081
JastTech
Training & Development Center
Office 402, Tech Park Road, Hinjewadi, Pune, Maharashtra 411057
JastTech
Training & Development Center
Millenium City - Tower I, Salt Lake, Kolkata, West Bengal 700091
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