Agentic Workflows & Multi-Agent Systems with LLMs Course
Master cutting-edge agentic workflows and multi-agent systems under expert guidance. Enroll in our specialized training program designed to equip you with comprehensive skills in autonomous task management, adaptive decision-making, and Machine Learning Operations best practices across industry-leading platforms.
- Available in:
- Malaysia
- Singapore
- United States
- India
- Indonesia
- Upcoming intakes:
- Nov 10, 2026
- Nov 10, 2026
- Nov 10, 2026
- Nov 11, 2026
- Nov 11, 2026
- Nov 11, 2026
- Nov 12, 2026
- Nov 12, 2026
- Nov 12, 2026
- Nov 13, 2026
- Nov 13, 2026
- Nov 13, 2026
- Nov 19, 2026
- Nov 20, 2026
- Nov 23, 2026
- Nov 23, 2026
- Nov 23, 2026
- Nov 24, 2026
- Nov 24, 2026
- Nov 24, 2026
- Nov 25, 2026
- Nov 25, 2026
- Nov 25, 2026
- Nov 26, 2026
- Nov 26, 2026
- Upcoming intakes:
- Nov 10, 2026
- Nov 10, 2026
- Nov 10, 2026
- Nov 11, 2026
- Nov 11, 2026
- Nov 11, 2026
- Nov 12, 2026
- Nov 12, 2026
- Nov 12, 2026
- Nov 13, 2026
- Nov 13, 2026
- Nov 13, 2026
- Nov 19, 2026
- Nov 20, 2026
- Nov 23, 2026
- Nov 23, 2026
- Nov 23, 2026
- Nov 24, 2026
- Nov 24, 2026
- Nov 24, 2026
- Nov 25, 2026
- Nov 25, 2026
- Nov 25, 2026
- Nov 26, 2026
- Nov 26, 2026
- Upcoming intakes:
- Nov 10, 2026
- Nov 10, 2026
- Nov 10, 2026
- Nov 11, 2026
- Nov 11, 2026
- Nov 11, 2026
- Nov 12, 2026
- Nov 12, 2026
- Nov 12, 2026
- Nov 13, 2026
- Nov 13, 2026
- Nov 13, 2026
- Nov 19, 2026
- Nov 20, 2026
- Nov 23, 2026
- Nov 23, 2026
- Nov 23, 2026
- Nov 24, 2026
- Nov 24, 2026
- Nov 24, 2026
- Nov 25, 2026
- Nov 25, 2026
- Nov 25, 2026
- Nov 26, 2026
- Nov 26, 2026
- Upcoming intakes:
- Nov 10, 2026
- Nov 10, 2026
- Nov 10, 2026
- Nov 11, 2026
- Nov 11, 2026
- Nov 11, 2026
- Nov 12, 2026
- Nov 12, 2026
- Nov 12, 2026
- Nov 13, 2026
- Nov 13, 2026
- Nov 13, 2026
- Nov 19, 2026
- Nov 20, 2026
- Nov 23, 2026
- Nov 23, 2026
- Nov 23, 2026
- Nov 24, 2026
- Nov 24, 2026
- Nov 24, 2026
- Nov 25, 2026
- Nov 25, 2026
- Nov 25, 2026
- Nov 26, 2026
- Nov 26, 2026
- Upcoming intakes:
- Nov 10, 2026
- Nov 10, 2026
- Nov 10, 2026
- Nov 11, 2026
- Nov 11, 2026
- Nov 11, 2026
- Nov 12, 2026
- Nov 12, 2026
- Nov 12, 2026
- Nov 13, 2026
- Nov 13, 2026
- Nov 13, 2026
- Nov 19, 2026
- Nov 20, 2026
- Nov 23, 2026
- Nov 23, 2026
- Nov 23, 2026
- Nov 24, 2026
- Nov 24, 2026
- Nov 24, 2026
- Nov 25, 2026
- Nov 25, 2026
- Nov 25, 2026
- Nov 26, 2026
- Nov 26, 2026
Training Provider Pricing
Pax:
Features
Target Audience
Methodologies
Subsidies

What you'll learn
- Implement hands-on agentic workflows with real-world scenario simulations
- Design agent triggers and orchestrate multi-agent workflow interactions
- Compare capabilities of Copilot Studio, UiPath, and Google Cloud platforms
- Apply Machine Learning Operations practices for model lifecycle management
- Analyze enterprise use cases for automation, compliance, and customer service
- Evaluate critical success factors from industry case study deployments
- Define core concepts of agentic workflows and multi-agent system architectures
Why should you attend?
This comprehensive course introduces learners to the transformative world of agentic workflows and multi-agent systems powered by Large Language Models. Students will explore fundamental concepts of autonomous task management and adaptive decision-making, understanding how these technologies revolutionize modern enterprise solutions through automation, compliance management, and enhanced customer service capabilities. The curriculum provides deep insights into three leading platforms: Copilot Studio, UiPath, and Google Cloud Platform, examining their unique approaches to agent orchestration and workflow design. Through detailed industry case studies, participants will analyze real-world implementations including audit automation in finance, invoice and claims processing, production error correction, recruitment optimization, and social profiling with graph analysis. Hands-on laboratory sessions form the core practical component, where students implement step-by-step agentic workflows, build agent triggers, design workflow logic, and orchestrate multi-agent actions. Real-world scenarios include automated compliance checks, document summarization, social profile matching, and transportation routing. Throughout the course, Machine Learning Operations best practices are emphasized, covering model lifecycle management, continuous integration and deployment, monitoring and logging, error handling, and feedback loops for model retraining and improvement, ensuring sustainable and scalable artificial intelligence agent operations.
Course Syllabus
Short Break
15 minsRecap and Q&A
15 minsRatings and Reviews
Instructor
Instructor
Instructor
Instructor
Instructor Reviews
Mohammad Mehdi Lotfinejad
Chief Data Officer & Data Science Trainer"Mehdi and I worked on several projects with company such as Petronas , Shell and CIMB Regional ETC. I must say Mehdi's training was highly appreciated by our clients as he was able to exhibit in full display his vast knowledge as a Data professional. I would highly recommend him to anyone looking for a top tier training expert."
"Not only knowledgeable but also having hands dirty on what he knows Friendly and building networks quickly."
"I had the pleasure of working with Mehdi together on some high-level initiatives such as the Petronas data scientist program and Shell's project to become a data-driven organization. During these projects, Mehdi received numerous accolades for his ability to share his knowledge and mentor up-and-coming data scientists. Based on our shared experiences, I have no hesitation in recommending Mehdi for any project or position he may be considered for."
FAQ
Frequently Asked Questions About This Course
- Public pricing: applies for individuals signing up from different companies.
- Corporate pricing: applies if a company wants to have an intake for its employees only.
- Training provider pricing: applies only for other training providers looking to hire our trainers and use our content. Our content has a licensing fee.
We will keep you updated on the status of the intake after you enroll.
Why should you attend?
This comprehensive course introduces learners to the transformative world of agentic workflows and multi-agent systems powered by Large Language Models. Students will explore fundamental concepts of autonomous task management and adaptive decision-making, understanding how these technologies revolutionize modern enterprise solutions through automation, compliance management, and enhanced customer service capabilities. The curriculum provides deep insights into three leading platforms: Copilot Studio, UiPath, and Google Cloud Platform, examining their unique approaches to agent orchestration and workflow design. Through detailed industry case studies, participants will analyze real-world implementations including audit automation in finance, invoice and claims processing, production error correction, recruitment optimization, and social profiling with graph analysis. Hands-on laboratory sessions form the core practical component, where students implement step-by-step agentic workflows, build agent triggers, design workflow logic, and orchestrate multi-agent actions. Real-world scenarios include automated compliance checks, document summarization, social profile matching, and transportation routing. Throughout the course, Machine Learning Operations best practices are emphasized, covering model lifecycle management, continuous integration and deployment, monitoring and logging, error handling, and feedback loops for model retraining and improvement, ensuring sustainable and scalable artificial intelligence agent operations.
What you'll learn
- Implement hands-on agentic workflows with real-world scenario simulations
- Design agent triggers and orchestrate multi-agent workflow interactions
- Compare capabilities of Copilot Studio, UiPath, and Google Cloud platforms
- Apply Machine Learning Operations practices for model lifecycle management
- Analyze enterprise use cases for automation, compliance, and customer service
- Evaluate critical success factors from industry case study deployments
- Define core concepts of agentic workflows and multi-agent system architectures
Course Syllabus
Short Break
15 minsRecap and Q&A
15 minsInstructor Reviews
Mohammad Mehdi Lotfinejad
Chief Data Officer & Data Science Trainer"Mehdi and I worked on several projects with company such as Petronas , Shell and CIMB Regional ETC. I must say Mehdi's training was highly appreciated by our clients as he was able to exhibit in full display his vast knowledge as a Data professional. I would highly recommend him to anyone looking for a top tier training expert."
"Not only knowledgeable but also having hands dirty on what he knows Friendly and building networks quickly."
"I had the pleasure of working with Mehdi together on some high-level initiatives such as the Petronas data scientist program and Shell's project to become a data-driven organization. During these projects, Mehdi received numerous accolades for his ability to share his knowledge and mentor up-and-coming data scientists. Based on our shared experiences, I have no hesitation in recommending Mehdi for any project or position he may be considered for."
Training Provider Pricing
Pax:
Features
Target Audience
Methodologies
Subsidies

Ratings and Reviews
Instructors
FAQ
Frequently Asked Questions About This Course
- Public pricing: applies for individuals signing up from different companies.
- Corporate pricing: applies if a company wants to have an intake for its employees only.
- Training provider pricing: applies only for other training providers looking to hire our trainers and use our content. Our content has a licensing fee.
We will keep you updated on the status of the intake after you enroll.
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