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Accelerating Design and Analysis in MATLAB Using Agentic AI
Accelerating Design and Analysis in MATLAB Using Agentic AI
A Practical Course to how Agentic AI can be integrated to MATLAB-based workflows
Course
Highlights
This course introduces how agentic AI can be integrated into MATLAB-based design workflows to accelerate analysis, implementation, and verification while keeping engineers in the loop. The concepts and techniques are designed to be transferable across large language models and AI tools, enabling participants to apply what they learn with the technologies that best fit their organization.
Who Should
Attend
This hands-on course is for intermediate users. It is especially useful for those who want to gain a fundamental understanding of how Agentic AI can help in solving complex engineering problems without removing the human-aspect.
Course
Prerequisites
Familiarity with the fundamentals of MATLAB is recommended. Undergraduate level mathematics and experience with basic computer operations is also recommended.
Course
Benefits
Upon the completion of the course, the participants will gain a comprehensive understanding of MATLAB-based design workflows, driving efficiency gains across analysis, implementation, and verification while preserving human oversight throughout.
Partners
Upcoming Program
- Please keep me posted on the next schedule
- Please contact me to arrange customized/ in-house training
Course Outline
Introduction to Agentic AI
Objective: Introduce the fundamentals of agentic AI and the key concepts needed to perform workflows in MATLAB.
- Chatbots vs. agentic AI systems
- The agentic loop: plan, generate, and evaluate
- Context in agentic AI
- Skills and Model Context Protocol (MCP)
- Overview of MathWorks agentic capabilities
Connecting MATLAB with AI Agents
Objective: Set up the MATLAB Agentic Toolkit and use it to complete tasks in MATLAB.
- MATLAB Agentic Toolkit installation
- MATLAB MCP Core Server and available MATLAB skills
- MCP interaction basics and key considerations
- Getting started example
Solving Engineering Problems in MATLAB with Agentic Workflows
Objective: Use agentic AI to solve real engineering problems in MATLAB with a human-in-the-loop approach.
- Project setup, scope, and source control
- Framing engineering problems for agentic workflows
- Formulating and executing a plan to solve an engineering problem
- Evaluating, testing, and documenting agent-generated MATLAB code
Skills, Context, and Customization
Objective: Create custom skills for repeatable workflows and understand how to scope them effectively.
- Overview of skills: files, structures, and context
- Authoring custom skills
- Defining structured workflows for repeatable behaviors
- Embedding domain expertise in skill design